Another way in which articulatory models of speech production differ is in the ways that they model the temporal coordination of articulatory movements. Coordination can be described at different levels, including the coordination of movements that contribute to a single constriction, as well as the coordination of movements that contribute to sequences of constrictions. Models differ on the information used to determine relative timing patterns, i.e., on whether they are based on relative timing vs. spatial characteristics vs. absolute timing. For example, in Fujimura's model, where faster consonantal gestures are superimposed on slower, vocalic gestures, coordination is based on relative timing: Consonantal elemental gestures are triggered at appropriate delays or lags from the syllable pulse, where the delays are specified as ratios of the syllable duration (Fujimura, 1994; Wilhelms-Tricarico, 2015).

Nam et al.'s (2010) theory of coupled oscillator model of coordination is also based on relative timing, that is, one constriction formation gesture is initiated when a particular planning oscillator phase of an earlier gesture is reached. On this view, if coupled planning oscillators speed up or slow down, the relative timing of gestures governed by the oscillators will be preserved. While Tilsen (2016) adopts this relative timing view for the coordination of onset consonants with syllable nuclei, he proposes a different mechanism based on spatial characteristics for the coordination of coda consonants with syllable nuclei. Tilsen (2016) proposes that coda consonant gestures are activated at the achievement of nucleus gestural target, i.e., on the basis of spatial information. In contrast, Šimko and Cummins' model proposes that gestural coordination and overlap are governed by costs of parsing (perceptual recoverability) and absolute time. For example, among other things, a higher parsing cost will encourage the speaker to make gestures more perceptually recoverable by making them less overlapped, and a higher time cost will make utterance duration shorter through increased overlap.

Whereas models of speech production have to date focused primarily on the relative timing of movement initiation, models available in the non-speech motor control literature suggest another possibility, namely coordination based primarily on the goal-related parts of movement, where movements are initiated at a time that ensures spatial and/or temporal accuracy (Harris and Wolpert, 1998; Todorov and Jordan, 2002; Tanaka et al., 2006). Similarly, on Lee's (1998, 2009) view, movements are controlled based on tau-coupling (tau = time-to-goalachievement at the current movement rate) to achieve their goal at a particular time. Thus, his model ensures synchronous goal achievement for all movements that are tau-coupled before the end of movement, but does not require that these movements begin synchronously. See Turk and Shattuck-Hufnagel (2020) for more discussion of Lee's General Tau Theory as applied to speech.

# Different Ways of Modeling Effects of Prosodic Structure on Timing

In spite of growing evidence that prosodic structure has a systematic influence on the durational patterns of virtually all known languages, relatively few articulatory models have explicit accounts of these and other contextual effects on timing. Here, we discuss models which have explicitly modeled prosodic effects in different ways.

Fujimura (1992 et seq.) framework assumes that phonological representations are expressed in terms of symbolic distinctive features, as well as symbolic representations of syllables (including their sub-constituents, i.e., onsets, nuclei and codas), and assumes higher-level prosodic constituency which can influence syllable durations in the vicinity of higher-level constituent boundaries. The syllable representations are mapped onto a "syllable pulse train," i.e., a series of (usually symmetric) triangles corresponding to syllables and pauses (if they occur), whose bases are contiguous. Triangle heights represent an appropriate magnitude multiplication factor (the pulse) which controls syllable prominence and phrasal boundary effects, and triangle bases represent syllable or pause duration. As a default, the apex angle is assumed to be the same for all triangles; therefore syllable triangle height correlates with syllable duration, so that longer duration and prominence are linked. In cases where additional lengthening is required, either the apex angle can be adjusted, or additional (half) triangles can be added to the utterance (Fujimura, 2002). Although this model provides a framework for modeling the influence of prosodic structure on correlated spatial and durational characteristics, it doesn't provide a way of determining what the syllable pulse heights

and apex angles (and hence the syllable durations) should be for a given context.

Šimko (2009), Šimko and Cummins's (2010, 2011), and Windmann's (2016) approaches are of note in this regard, because they propose a principled cost-minimization mechanism for determining durational properties of speech, based on Optimal Control Theory. Šimko and Cummins' Embodied Task Dynamics model is a development of the Task Dynamics model used in AP/TD, in which the articulators are assigned masses, and optimization is used to determine model parameter values. In this model, gestural activation onset and offset timing (specified in solar time units) and system stiffness (where system stiffness is a scaling factor for gestural and "speech-ready" stiffness5 ) are optimized using three costs: An effort cost, a perceptual (parsing) cost, and a time cost which is a linear function of utterance duration in milliseconds. Benuš and Šimko (2014) ˇ showed that locally decreasing the duration cost in the vicinity of a phrase boundary can be used to model boundary-related lengthening in Slovak m(#)abi and m(#)iba sequences6 .

Although Šimko and Cummins' approach is based on Articulatory Phonology, it differs from AP in the use of solar timing units, which are used for the specification of its time cost, as well as for the specification of gestural activation durations which result from their optimization procedure. In contrast, Articulatory Phonology in the Task Dynamics framework (Byrd and Saltzman, 2003; Saltzman et al., 2008) provides an approach in which solar timing units are not required, and where surface timing patterns are fully emergent from phonology-specific processes. In their approach, lengthening effects due to prosodic structure are modeled as adjustments of gestural activation durations. Gestural activation durations are not specified in milliseconds, but rather in proportions of gestural planning oscillator periods. At a default rate of speech, gestural activation duration corresponds to gestural mass-spring settling time, i.e., the time required for a gesture to approximate its target. In particular prosodic positions, such as phrase-boundary-adjacent position, or at slower speech rates, the default gestural activations are stretched (Byrd and Saltzman, 2003). This stretching is implemented in later versions of the theory (Saltzman et al., 2008) by slowing the frequency of the gestural planning oscillators. Analogously, at faster rates of speech, or in unstressed positions, the default gestural activations are shortened by speeding up the frequency of the gestural planning oscillators. This approach has been used successfully to model effects of prominence, boundary-adjacency, and poly-subconstituent shortening.

Tilsen's recent development of AP (Tilsen, 2018) provides another mechanism for prominence-related lengthening, based on feedback about target approximation. In this model, one mechanism for ending gestural activation is the suppression of gestural activation after targets are approximated. In this proposal, prominent syllables and syllables produced at a slow speech rate are proposed to result from a high degree of reliance on external feedback about target approximation.

# EVIDENCE FROM THE LITERATURE THAT RELATES TO THESE CHARACTERISTICS AND CONSTRAINS THE CHOICE OF APPROPRIATE MODEL

The previous section showed substantial differences among existing models of speech articulation control timing patterns. Many of these differences derive from choices about the general architecture of the system and about the nature of phonological representations that encode contrast, phonological equivalence and prosodic structure. In spite of the differences, these models all generate plausible articulatory trajectories, at least in some contexts. How can they be distinguished? In this section, we discuss phenomena which bear on this question, focusing on the issues of (1) emergent vs. specified surface timing patterns (2) spatio-temporal representations vs. the independent representation of timing information (3) the use of phonology-specific vs. general-purpose timekeepers, (4) spatio-temporal representations vs. symbolic representations, (5) movement coordination, and (6) modeling effects of prosodic structure.

Evidence bearing on these issues motivates an alternative approach to modeling timing control, i.e., a phonology-extrinsic approach based on symbolic phonological representations in a Phonological Planning Component, with specifications for surface durations that are planned in a Phonetic Planning Component that is separate from the Phonological Planning Component. The first two phenomena, (1) constraints on lengthening due to phrasal prosody, and (2) different strategies for controlling rate of speech, boundary-related lengthening and quantity, suggest that surface durations are explicitly represented. As a result, they present a challenge to approaches to timing in which surface durations emerge without explicit representation; moreover, the second phenomenon suggests that surface durations can be specified independently of spatial characteristics, since the timing patterns are the same while the spatial characteristics vary. The third phenomenon, (3) more timing variability for longer duration intervals in speech and nonspeech behavior, suggests the involvement of a noisy generalpurpose timekeeping mechanism in the speech production process, in which longer durations intervals are associated with more timing variability due to accumulated noise. Finally, the fourth phenomenon (4) less timing variability at movement endpoints compared to other parts of movement, challenges the concept of spatio-temporal representations, and suggests that movement coordination is based on goal-related parts

5 Speech-ready stiffness is analogous to the stiffness of the neutral attractor in the AP/TD framework, except that speech-ready dynamics is always turned on, even when gestures are active, and the speech-ready stiffness of individual articulators can be manipulated according to requirements for higher precision (Šimko, 2009). The speech-ready position is assumed to be "an average constellation with regard to the entire set of mastered gestures" (Šimko et al., 2014, p. 133).

6Windmann et al. (2015) and Windmann (2016) show how this same general approach, i.e., minimizing costs of effort, (mis)-parsing and time, can be used to model durational effects of prominence (phrasal prominence, lexical prominence, and their interaction) and polysyllabic shortening, as well as interactions with speaking rate, as measured from the acoustic signal.

of movement rather than onsets. Taken together, these four phenomena support the alternative view that speech production planning is based on symbolic phonological representations and includes separate components for Phonological and Phonetic Planning, as well as a third, Motor-Sensory Implementation component in which speech movements and acoustics are monitored and adjusted to ensure that spatial and timing goals are achieved appropriately (Houde and Nagarajan, 2011; Guenther, 2016).

# Constraints on Lengthening Due to Phrasal Prosody Suggest That Surface Timing Patterns Are Represented, and Not Emergent

In Northern Finnish and Dinka, which have a phonemic quantity contrast, the phonemically short vowels are lengthened less than the long vowels, in prosodic contexts such as phrase-final position (Remijsen and Gilley, 2008; Nakai et al., 2009, 2012). For example, as **Figure 1** shows, the magnitude of final, accentual, and combined lengthening of phonemically short vowels in Northern Finnish is restricted compared to lengthening on phonemically long vowels (Nakai et al., 2009, 2012). This suggests that speakers of this language explicitly constrain the surface durations of phonemically short vowels to maintain the duration contrast with longer vowels.

In this figure, VV refers to a phonemically long vowel, and V to a phonemically short vowel. Note that in the last syllable of CVCV(C) words, cf. the left-hand side of **Figure 1B**, the phonemically short vowel shows a greatly reduced magnitude of combined accentual + final lengthening (17%) compared to the phonemically long vowel in the same context (68%). The lengthening pattern on this so-called "half-long vowel"7 is suggestive of a constraint resulting in a surface duration of phonemically short vowels of < ca. 140 ms, at least at this speaking rate, supporting the view that the (phonemically short) half-long vowels are lengthened less than the long vowels to avoid endangering the phonemic contrast between short and long vowels in this language. Two types of empirical evidence for a constraint on the surface duration of phonemically short vowels are provided in Nakai et al. (2009, 2012). First, Nakai et al. (2009) found a negative correlation between phrasemedial duration and the amount of final lengthening for V2 in CV1CV2 structures. One might initially imagine a mechanism by which speakers could learn to lengthen phonemically short vowels less to avoid confusion in their listeners, without explicitly representing a durational constraint. However, this potential solution is ruled out by the observation that speakers adjust the amount of lengthening for their phonemically short vowels in a way that maintains a surface durational distinction. That is, phonemically short vowels that are shorter are lengthened more, and phonemically short vowels that are longer are lengthened less, showing evidence of a surface duration constraint. Further support for a surface duration constraint

comes from Nakai et al. (2012)'s study of final lengthening and accentual lengthening, which combine sub-additively for V2 in CV1CV2. A constraint on lengthening of this type is difficult to express in a system that does not explicitly represent surface durations.

The final lengthening patterns in Dinka, a Nilotic language, are also consistent with this type of constraint. This language has a three-level quantity system, and vowels of short and medium quantities are lengthened less than the long vowels, in phrase-final position, a prosodic context that requires duration lengthening (see **Figure 2**, reproduced from Remijsen and Gilley, 2008).

The results reviewed here suggest that the explanation relates to surface durational information which is represented in the minds of speakers, and is involved in the maintenance of phonemic contrasts. These results are difficult to account for

7The "half-long vowel" is a phonemically short vowel whose phrase-medial duration is intermediate between that of a non-word-final phonemically short vowel and that of the long vowel (VV).

in models in which surface durations are the emergent output of activation interval durations + phonology-intrinsic clockslowing adjustments, are not explicitly represented, and so cannot be invoked as constraints on lengthening.

# Different Strategies for Manipulating Durations (in e.g., Rate of Speech, Boundary-Related Lengthening, and Quantity), Suggest That Surface Timing Goals Are Explicitly Represented, and Not Emergent

The explicit representation of surface duration requirements is supported by another type of evidence, related to the implementation of overall rate of speech as well as to boundaryrelated lengthening, and to duration-related quantity differences. This evidence suggests that speakers specify surface interval duration requirements as goals of speech production, and meet these requirements using a variety of different strategies. The equivalence of these strategies goes unexplained in theories that cannot represent surface durations. That is, the only thing shared by all of the different strategies is their equivalent effects on surface durations.

One example of this kind of evidence is that, when asked to speak quickly, speakers achieve surface durations using a wide variety of strategies. Although it is often the case that speakers accomplish this task by reducing the number and/or durations of pauses at fast rates, other strategies have also been observed. For example, acoustic studies show that speakers may manipulate the number of pauses, but not the durations, or vice versa (Fletcher, 1987; Trouvain, 1999). Likewise, kinematic studies reveal that, although the peak velocity/distance relationship for movements is often higher at fast rates, some speakers achieve faster rates by increasing articulatory speed (peak velocity), while other speakers achieve this by reducing movement distance (Abbs, 1973; Ostry and Munhall, 1985; Engstrand, 1988; Goozée et al., 2003; see Berry, 2011 for a review). And while many speakers show increased articulatory overlap at fast rates, not all speakers do (Engstrand, 1988; Boyce et al., 1990; Shaiman et al., 1995; Byrd and Tan, 1996; Shaiman, 2001, 2002; all cited in Berry, 2011).

What these studies show is that speakers respond differently to instructions when asked to speak quickly, but in all cases achieve shorter utterance durations. We cannot see how the equivalence of their strategies can be expressed without reference to the surface duration goals of these utterances. Similar findings of different strategies for achieving similar surface duration goals have been observed for quantity differences and phrase-final lengthening (Edwards et al., 1991; Hertrich and Ackermann, 1997). Hertrich and Ackermann's (1997) findings are of particular note because they show that the same speaker can use different strategies to achieve durational differences in different contexts. For example, Hertrich and Ackermann (1997) showed that the same speaker used different strategies to achieve the phonemically short vs. long distinction for different vowels. That is, some speakers showed a longer opening movement for /A:/ compared to /A/, but a predominate pattern of a longer initial part of the closing movement for /u:/ compared to /u/. Similarly, Edwards et al. (1991) showed that the same speakers used different strategies for achieving longer surface durations in phrase-final position (compared to phrase-medial position) at different rates of speech. That is, at faster rates, they slowed articulatory speed in phrase-final position, but at a slow rate, they kept speed constant and held the articulators in quasisteady states.

Taken together, these studies of strategies for adjusting durations for rate of speech, vowel quantity, and final lengthening suggest that surface durations are speech production goals that can be achieved in a variety of ways. This type of motor equivalence supports the view that (1) surface duration requirements can be specified as part of the speech production process, and (2) these durational requirements or goals are separately specified from how the goals are achieved. Particularly telling are cases where the same speakers show different articulatory strategies for achieving similar durational patterns in different speaking-rate contexts.

These findings support models in which (1) surface duration goals (or costs) for intervals can be explicitly represented during phonetic planning, and (2) these goals are specified separately from how the goals are achieved articulatorily. This type of model architecture would make it possible for the same goal to be achieved in a variety of ways.

# More Timing Variability for Longer Duration Intervals Suggests the Involvement of General-Purpose Rather Than Phonology-Specific Timekeeping Mechanisms

The previous sections presented evidence suggesting that speakers explicitly represent surface timing goals, and can accomplish those timing goals in many different ways. We argued that emergent timing mechanisms specific to the task of speaking cannot account for the observed behavior, raising the question of what kind of alternative mechanism could support the planning of such intervals. This section presents evidence from timing variability that suggests an answer: general purpose timing mechanisms that could be used in specifying and planning surface durations in speech.

Many types of timed behaviors show what is known as "the scalar property," a relationship between interval duration and variability that tends to follow Weber's law, resulting in an approximately constant coefficient of variation (SD/mean) over a range of intervals. Getty (1975) proposed that variability in interval durations arises from two sources of noise (1) a duration-dependent source, thought to be the consequence of noise in a timekeeping process, and thus to increase with the duration of the interval, and (2) a source of variability due to noise in the motor system, assumed to be constant regardless of the duration of the interval. This proposal provided an account of the higher coefficient of variation (SD/mean) observed for shorter intervals (up to approximately 200 ms) as compared to longer intervals (approximately 200– 1300 ms). For a review of different modeling approaches to general purpose timekeepers with accounts of timing variability, see Schöner (2002).

Behaviors showing timing variability that grows with interval duration include:

consonant target-to-second consonant release). Similar findings are reported in the speech literature for intervals measured from landmarks (Stevens, 2002) in the acoustic signal. For example, phonemic quantity differences (Dinka: Remijsen and Gilley, 2008; N. Finnish: Nakai et al., 2012); Chen (2006) for focused vs. non-focused constituents in Mandarin; Nakai et al. (2012) for final and phrasally accented vs. non-final, non-accented intervals in N. Finnish; and Lefkowitz (2017) for a linear relationship between standard deviation and mean duration of vowel intervals across a very wide range of contexts in an English experiment.

Findings of greater timing variability in phrase-final and/or phrasally prominent positions are thus consistent with the view that speech makes use of a general-purpose timekeeping mechanism, with variability that is proportional to the surface duration of the timed interval, as suggested by Gallistel, 1999; Gallistel and Gibbon, 2000; Jones and Wearden, 2004; Shouval et al., 2014; and others). The law applies to timing behavior in many different tasks (non-speech) and speech, and in perception and in production. Whatever mechanism accounts for this law therefore appears to be general across all of these tasks and behaviors. General purpose timekeeping mechanisms thus provide a unified account of timing variability for all timed intervals; see below for further discussion.

# The Observation of Less Timing Variability at Movement Endpoints Than at Other Parts of Movement Challenges (Spatio-)Temporal Phonological Representations, and Supports a Model of Speech Production Based on Symbolic Phonological Representations

The sections above presented three types of evidence for the representation of surface time intervals in the planning of movements – a constraint on the surface durations of phonemically short vowels in some quantity languages; multiple articulatory strategies for attaining appropriate acoustic durational patterns, suggesting that those patterns themselves are the goals of the movement, and the increase in variability with longer intervals, suggesting that those intervals are generated using a general purpose phonology-extrinsic timing mechanism that operates in units of surface (solar) time, rather than in phonology-intrinsic timing mechanisms operating in nonsolar time units. In this section we present an argument for symbolic (as opposed to spatio-temporal) phonological representations. The evidence for this argument comes from observations of less timing variability at particular parts of movement, which are most behaviorally meaningful. This evidence supports symbolic representations because it requires a representation of the most behaviorally meaningful part of movement so it can be prioritized for timing accuracy. It supports symbolic representations because they can map onto a part of movement that relates most directly to

the achievement of a phonological goal, and can therefore be prioritized. Such symbolic representations require the specification of timing and other phonetic characteristics in a separate phonetic planning component. Thus, this evidence for symbolic phonological representations provides a fourth argument for the use of phonology-extrinsic time, because there are no time specifications in the phonology.

Evidence for the representation of individual parts of movement, so that their timing can be prioritized, comes from a number of sources. In his 1998 paper, Dave Lee notes: "it is frequently not critical when a movement starts – just so long as it does not start too late. For example, an experienced driver who knows the car and road conditions can start braking safely for an obstacle a bit later than an inexperienced driver." This observation suggests that the timing of the part of movement most closely related to the goal attainment should be less variable than the timing of other parts of movement8 . This section presents evidence from repeated movements elicited in controlled laboratory experiments that that confirms Lee's prediction.

Many findings in the literature are consistent with the observation that the timing of movement endpoints can be less variable than for other parts of a movement, even for repeated movements that have the same movement path9 . For example, Gentner et al. (1980) study of keypress timing in typing found lower consistency in the start times of key press movements, as compared to the end times, for two typed repetitions of the same sentence, performed by an experienced typist. The median difference in start times was 58 ms, compared to a difference of 10 ms for end times.

Additional evidence for lower timing variability at movement endpoint can be found in periodic tapping data (Billon et al., 1996; Spencer et al., 2003; Zelaznik and Rosenbaum, 2010), For example, Spencer et al. (2003) found that timing variability in repetitive tapping showed lower variance at finger touchdown as compared with the time of peak velocity. Zelaznik and Rosenbaum (2010) found similar results for tapping, in that timing variability of contact with the tapping surface was lower than that of maximum finger extension. Interestingly, however, both Spencer et al. (2003) and Zelaznik and Rosenbaum (2010) found a different pattern of results for circle drawing, that is, no evidence for differences in timing accuracy at different points in the circle cycle. For example, in Zelaznik and Rosenbaum (2010), the variability at cycle onset (0◦ ) was no different from timing variability at a spatial location opposite to cycle onset (180◦ ). This evidence is consistent with the emergent timing view of continuous circle drawing, that is, that timing in such tasks is primarily emergent from dynamic characteristics and has minimum involvement from a timekeeping mechanism. See Zelaznik and Rosenbaum (2010) and Studenka et al. (2013) for evidence less consistent with emergent timing for circle drawing when it creates a perceptual (auditory or tactile) event that could be thought of as the goal of the movement, consistent with the idea that when salient timing-related events can be identified, general-purpose timing mechanisms are likely to be invoked; see Repp (2008) and Repp and Steinman (2010) for more nuanced discussions.

Although speech production data on this topic is limited, the available data show timing variability patterns that are consistent with those observed for typing and periodic tapping; that is, they show less timing variability at goal-related parts of movement, such as movement endpoint, than at other parts of movement, such as the movement onset. Because it is often difficult to accurately diagnose movement onset times for a particular articulator when its movements may have been governed by multiple phonemes, Perkell and Matthies (1992) studied timing variability for upper lip protrusion movements during spoken /i\_u/ sequences, where intervening consonants were /s,t,k/ and /h/, which are not normally associated with upper lip movement. The number of intervocalic consonants was varied systematically. Furthermore, to be sure that these intervening consonants did not have upper lip movement associated with them, they carefully examined upper lip protrusion traces during /i\_i/ contexts. Because they observed that /s/ did in fact have some idiosyncratic upper lip movement associated with it during the production of /isi/, they removed data with intervening /s/ from their analysis. As an additional precaution to ensure that their measure for movement onset was under sole control of the following /u/, they identified movement onset not as a point of velocity zero, but as the point of acceleration maximum, i.e., a time point clearly associated with movement toward the /u/ target. After all of these precautions to ensure that the measured upper lip protrusion timing data was due to the production of /u/ alone, they still found more variability for the timing of acceleration maximum as compared to the timing of maximum protrusion. As shown in **Figures 3**, **4** 10, they observed lower variability in the timing of movement endpoint (maximum protrusion) relative to voicing onset for /u/, as compared to the timing of maximum acceleration, relative to voicing onset for the same vowel. This pattern suggests a tighter temporal coordination of maximum lip protrusion (movement endpoint) with voicing onset than of lip protrusion movement onset (max. acceleration) to voicing onset, and suggests that the timing of movement endpoint has higher priority than the timing of movement onset in these speech movements. This pattern suggests that having maximally protruded lips at the onset of voicing is the prioritized goal.

The view that the timing of the most behaviorally meaningful part of movement is given highest priority is supported by Gafos et al. (2019) evidence relating to the coordination of consonant clusters [bd, db, dg, gd, br, rb, kr, rk, kl, lk, lb,

8 It is often the case that the part of movement most closely related to the goal in speech is the movement endpoint. For example, the endpoint of lip protrusion is most closely to the goal for /u/, but for geminate consonants followed by a vowel, the timing of the beginning of the release movement toward the following vowel may be the most relevant for signaling the geminate status of the consonant.

9 In cases where movements are of different distances, additional variability in the timing of movement onsets might be expected, since Fitts' (1954) law dictates longer duration movements for longer distances (in spite of higher velocities for these movements) as long as accuracy or target width remains constant.

10Although they do not report magnitudes of variability, e.g., in standard deviations, the difference in variability is clear on visual inspection of the figure.

FIGURE 3 | Reproduced from Perkell and Matthies (1992), with the permission of AIP Publishing. Caption as in the original: Schematic illustration of data extraction. From top to bottom: (1) a segment of the acoustic signal (ACOUSTIC), (2) lip protrusion (PROTRUSION), (3) lip velocity (VELOCITY), and (4) lip acceleration (ACCELERATION) vs. time. Acoustic events in the time-expanded acoustic signal are end of the /i/ (iEnd) and beginning of the /u/ (Vbeg). Movement events are: movement beginning (mBeg), movement end (mEnd), and maximum acceleration (AccMax).

and nk] in three different positions-in-word in Moroccan Arabic. This evidence shows that movements toward C2 exhibit higher amplitude-normalized peak velocity the later they begin relative to C2 release. This finding supports the idea that speakers ensure appropriate movement velocity in order to achieve the behaviorally meaningful part of C2 (possibly its release) on time.

Additional evidence for the prioritization of timing accuracy at goal-related parts of movement can be found in speechrelated manual gesture (Leonard and Cummins, 2011). They found less timing variability at a point of maximum hand + arm extension compared to other parts of movement, for hand + arm "beat" gestures that co-occur with speech. They recorded hand + arm movements (by recording the movement of an LED marker attached to the base of the thumb) while a speaker read two repetitions of three short fables. They found that the point of maximum extension of the hand before retraction had the least timing variability compared to other parts of movement (movement onset, peak velocity of extension, peak velocity of retraction and movement retraction end), measured relative to landmarks in the stressed syllable in each word. These findings suggest that the point of maximum extension is the part of movement which is coordinated with stressed syllables, as opposed to the onset of movement.

Taken together, these results suggest that particular part(s) of movement can be more task-relevant, or "behaviorally meaningful" than other parts of movement (cf. Shaffer, 1982; Semjen, 1992; Billon et al., 1996, for timing). They are also consistent with the view that the most task-relevant features of motor performance are prioritized for accuracy and therefore have the least variability, as proposed in Todorov and Jordan's (2002, 2003) Minimal Intervention principle (cf. Winter, 1984; Lacquaniti and Maioli, 1994; Scholz and Schöner, 1999; discussed in Scott, 2004). Semjen (1992) makes this point about the control of finger movements in typing: "When copying a text, the typist probably attempts to produce the successive keystrokes fluently and at a fast sustained rate. The typist would thus anticipate the temporal properties of a sequence of behaviorally meaningful events, rather than the characteristics of the individual movements producing them. . . . We are thus led to a notion of multi-level temporal organization in serial movements, with some level(s) being more directly related to the subject's intentions than others." (Semjen, 1992, p. 248).

Along these lines, findings of greater temporal accuracy at particular parts of movement suggest that these parts of movement are "behaviorally meaningful" and are more closely related to the speaker's goals for the utterance. For example, the various movements of the articulators must be coordinated to create particular configurations at appropriate times, or the goal of signaling the features, sounds and words of the utterance will not be met. Other, less behaviorally meaningful parts of movement are produced in service of achieving those goals.

The finding that goal-related parts of movement are more accurate/less variable than other parts of a movement requires the representation of a movement goal as separate from the way the movement is achieved, as well as a mechanism to ensure more precise timing accuracy at the goal-related part of movement. As discussed below, this challenges models with spatio-temporal representations in which there is no distinction between the goal of a movement and the way it is achieved, because without this distinction, the phonological representation (and thus the phonological goal) actually corresponds to an entire movement trajectory (apart from starting position). As a result, the most behaviorally meaningful part of movement is not separately identified and therefore can't be prioritized. In contrast, it supports models which make use of symbolic representations in the phonology. This is because symbolic representations can map onto a particular part of movement that relates most directly to the achievement of a (symbolic) phonological goal, and can therefore be prioritized for accuracy.

# The Observation of Less Timing Variability at Movement Endpoints Than at Other Parts of Movement Challenges Onset-Based Movement Coordination

Findings of greater temporal precision at endpoints compared to other parts of movement also provide evidence for the nature of movement coordination. It suggests that movement coordination is based on goal-related part(s) of movement (often the endpoint), and requires a way to ensure timing accuracy at the goal-related parts of movement. Additional evidence for goalrelated, endpoint-based coordination in non-speech activity can be found in Gentner et al. (1980), Bootsma and van Wieringen (1990), Kazennikov et al. (1994), Haggard and Wing (1998), Craig et al. (2005), and Katsumata and Russell (2012); endpoint-based coordination and its implications for speech timing models are discussed at length in Turk and Shattuck-Hufnagel (2020).

# Summary of Evidence

To summarize, the above evidence suggests that (1) speakers represent and specify surface duration goals for intervals, (2) in specifying surface durations, speakers make use of generalpurpose timekeeping mechanisms, and (3) speakers separately represent, and prioritize for timing coordination accuracy, the most behaviorally meaningful parts of movement. This evidence is inconsistent with approaches to speech production in which (1) surface timing characteristics are only emergent and not represented, (2) timing units do not relate straightforwardly to solar time, and (3) phonological representations define the timing of all parts of a movement trajectory. Instead, the evidence presented above motivates speech production models that make use of (1) general-purpose timekeeping mechanisms to represent and specify surface durations, and (2) have a way of representing behaviorally meaningful parts of movement separately from other parts of movement, so that they can prioritized for timing accuracy, and be coordinated with other events. In the following sections, we discuss why AP/TD, the model with the most comprehensive account of articulatory timing behavior, is challenged by these phenomena, and why these phenomena support a model based on symbolic representations and phonology-extrinsic timing, with three components: (1) Phonological Planning, (2) Phonetic Planning, and (3) Motor-Sensory Implementation.

# DISCUSSION OF AP/TD AS THE MOST COMPREHENSIVE, BEST-WORKED OUT MODEL OF TIMING AND WHY IT IS NEVERTHELESS CHALLENGED BY THESE FINDINGS

Articulatory Phonology in the Task Dynamics framework is currently the model with the most comprehensive coverage of timing effects in speech, including smooth, single-peaked velocity profiles, durations of gestural (constriction-forming) movements, coordination, boundary- and prominence-related lengthening, poly-sub-constituent shortening, and rate of speech. Key features of its approach to timing include (1) the use of spatio-temporal phonological representations, called gestures, as units of lexical contrast and phonological equivalence, (2) phonology-intrinsic timekeeping and gestural activation adjustment mechanisms to account for systematic contextual variability, (3) surface timing characteristics that emerge from the phonology without any representation of their durations in solar timing units. Its use of spatio-temporal phonological representations as units of lexical contrast and phonological equivalence, as well its commitment to emergent timing, are both motivated by the desire to avoid translation between phonological data structures to different data structures in phonetics (Fowler et al., 1980). That is, it is motivated by the desire to avoid having a phonetic planning component that is separate from the phonology. A substantial challenge of this approach is how to account for systematic variability in the production of members of the same phonological category, while maintaining their phonological equivalence. Its solution to this challenge involves (1) a definition of the gesture which allows for different gestural starting positions; (2) phonology-intrinsic mechanisms for adjusting the interval of time that a gesture is active (its gestural activation interval); and (3) mechanisms for controlling patterns of gestural overlap, and articulatory activity that it governs. Together, these mechanisms give rise to surface contextual variability without altering the defining characteristics of each gesture, i.e., its equation of motion and coefficient values (apart from starting position).

In this section, we lay out AP/TD's approach to this challenge in more detail. Gestures are modeled by a second order massspring equation of oscillatory motion, critically damped so that the mass approximates a target position but doesn't oscillate. Target and stiffness coefficient values vary across gestural categories (target values differ for each gesture; stiffness values differ for consonants vs. vowels), whereas damping and mass coefficients are the same for all gestures (mass is set to 1, damping has a value that ensures critical damping). Gestural starting position is determined by previous context. How long each gesture is active (the gestural activation interval) is controlled by a system of coupled limit-cycle oscillators, i.e., gestural planning + syllable, foot and phrase oscillators (Saltzman et al., 2008, but see Tilsen, 2013, 2016, 2018, for a different approach). Because the gestural activation interval is defined as a proportion of a gestural planning oscillator cycle, the oscillation rate of the gestural planning + suprasegmental oscillator ensemble determines the duration of the gestural activation interval. A default oscillation rate gives rise to activation intervals which are long enough for gestures to approximate their targets. Longer intervals at phrase edges and in prominent positions are achieved via a mechanism which slows the AP/TD "clock" in these positions without adding timing units (see Byrd and Saltzman, 2003 for an early Pi gesture proposal; Saltzman et al., 2008 for a later MuT proposal which slows the gestural planning + suprasegmental oscillator ensemble oscillation rate); shorter intervals for, e.g., faster rates of speech, are achieved by speeding up the planning + suprasegmental oscillator "clock"

(Saltzman et al., 2008), which may result in undershoot of the stored gestural target.

In this model, surface timing characteristics are the emergent output of fixed gestural characteristics (e.g., the time it takes for the gestural mass-spring system to approximate its target position), as well as utterance-specific gestural activation interval specifications (determined by the oscillation frequency of the planning + suprasegmental oscillator ensemble and the shape of the activation interval on- and off-ramps). Articulatory and acoustic surface timing characteristics (as measurable in solar timing units) emerge from this system without the involvement of any phonology-extrinsic, general-purpose timekeeping mechanisms that operate with such units. Because the planning + suprasegmental oscillator "clock" frequency is changed in particular phrasal positions and for different overall speech rates, there is no straightforward correspondence between planning + suprasegmental oscillator "clock" timing units and solar timing units.

Despite the general success of this model in accounting for timing effects in speech, it is challenged by the findings presented in previous sections. We will briefly review those challenges in light of the characteristics of AP/TD described just above.

# Constraints on Lengthening Due to Phrasal Prosody

Constraints on lengthening phonemically short vowels in prosodic contexts where lengthening occurs are difficult to explain in AP/TD. On the assumption that the lexical difference between short and long vowels in AP/TD is a difference in phonological representation, e.g., of one vs. two gestures, or of a gesture associated with one vs. two moras, both phonemically short and long vowels could be lengthened by the same amount and the lexical distinction would be maintained. But, that is not what is observed. Instead, less lengthening is found on the short vowel. This can only be accomplished in AP/TD by an ad hoc imposition of a smaller amount of lengthening on the short vowel, e.g., via a Pi/MuT gesture with a smaller height for phonemically short vowels, or by proposing a Pi/MuT phasing solution, in which (1) a Pi/MuT gesture is aligned to the onset of the final syllable, (2) the Pi/MuT gesture is of fixed duration, and (3) the Pi/MuT gesture activation increases over time. However, although AP/TD provides these possible mechanisms for implementing different degrees of lengthening on phonemically short vs. long vowels, it provides no explanation of the phenomenon. That is, AP/TD provides no explanation for why phonemically short vowels should have Pi/MuT gestures with shorter heights associated with them, or why a Pi/MuT gesture would need to be phased with respect to the onset of a final syllable in Finnish, but not in other languages. For example, in non-quantity languages with reduced vs. full vowels, the proportional magnitude of boundary-related lengthening is not constrained for short duration, reduced vowels (e.g., the unstressed vowel in Thomas) as compared to longer duration full-vowels (e.g., the second syllable vowel in Brookline, Turk and Shattuck-Hufnagel, 2007). This suggests alignment of a Pi/MuT gesture with the end of a word (Byrd and Saltzman, 2003), rather than with the onset of the final syllable.

In contrast to AP/TD, which has difficulty explaining the constraint on final lengthening on phonemically short vowels in quantity languages, theories which allow for the representation of surface durations provide a possible explanation. That is, smaller amounts of lengthening on phonemically short vowels can be explained if there is a constraint that preserves the surface duration distinction between phonemically short and long vowels.

To put it another way, if vowels of different quantities had the same phonological representation, the constraint on prosodic lengthening for short (and medium) vowels could be expressed as a constraint on the degree of AP/TD "clock" slowing. But, in this case, where the two types of vowels had the same phonological representation (i.e., the same number and type of gesture), there would be no way to express the lexical contrast. Instead, because AP/TD differentiates phonological categories with gestures, we assume that the phonological contrast between these different types of vowels is expressed in the lexicon as one vs. two or more gestures or perhaps as a single gesture associated with one vs. two moras. As a result, the surface durations of these vowels is due to a combination of (1) the number of AP/TD timing units in their gestural activation intervals (determined by the number of gestures or the number of moras), and (2) the degree of clock slowing (determined by the Pi or MuT gesture). In this type of system, there is no way to account for the apparent surface duration constraint on the lengthening of contrastively short vowels, because this constraint relates to the emergent result of the interaction of two different AP/TD properties: (1) the number of AP/TD "clock" timing units in the activation interval and (2) the degree of clock slowing, which together result in surface duration in solar time. AP/TD can refer to each of these quantities, but has no way of representing the fact that they both affect surface duration, that is, it has no way of relating their equivalent effects on a desired surface duration. AP/TD therefore has no explanation for different degrees of clock slowing on phonemically short vs. long vowels, because the explanation has to do with the maintenance of a surface duration distinction.

In sum, while the AP/TD phonology-intrinsic "clock" slowing Pi- and MuT-gestures might provide a mechanism to specify different degrees of phrase-final- or phrasal-accentrelated lengthening for contrastively short (or medium) vs. long vowels, AP/TD has no representation of the surface duration outcomes of such activation interval adjustments. Consequently, it does not predict that a difference in lengthening degree for phonemically short vs. long vowels should occur, and does not offer an explanation for why contrastively short vowels are lengthened less, nor for the degree of lengthening these contrastively short vowels exhibit. Furthermore, adding a representation of the surface duration outcome would not be desirable in this framework, because this would involve a "translation" of phonology-intrinsic time into (phonetic) surface durations, something that the authors of the framework (and its antecedents) have tried to avoid (Fowler et al., 1980).

# Different Strategies for Manipulating Durations in, e.g., Rate of Speech, Boundary-Related Lengthening, and Quantity

This evidence suggests the equivalence between different temporal and spatio-temporal strategies that accomplish the same surface duration goal. It is challenging to account for in AP/TD for two reasons: (1) AP/TD doesn't have a representation of surface duration goals, and (2) AP/TD doesn't make a distinction between goals and how the goals are achieved. In this model, there are several different mechanisms that result in longer surface durations, e.g., differences in gestural stiffness, slowing gestural planning oscillators for longer gestural activation intervals, and adding gestures. However, because the model cannot refer to surface durations, the explanatory fact that these mechanisms all have a similar surface duration result is not captured in the model. Furthermore, in AP/TD, spatial and temporal aspects of movement are not independent: both are determined by the same phonological plan. Thus, it is difficult to account for behavior in which a speaker obtains the same temporal result with different spatial paths. Put another way, it is difficult for this model to account for the equivalence of rates, of quantities, and of lengthening (e.g., in final position) when these are achieved in different temporal and/or spatial manners, because this model doesn't allow the specification of temporal goals as distinct from the way they are achieved. That is, in AP/TD this equivalence can only arise by chance, because achieving the same surface duration pattern result can't be specified as the goal of the speaker.

# More Timing Variability for Longer Duration Intervals

Findings of greater timing variability in phrase-final and in prominent positions are inconsistent with AP/TD's account of boundary-related and prominence-related lengthening, with its lack of surface durations, and with its lack of generalpurpose timekeeping mechanisms. To see why this is so, first consider the details of how timing is adjusted in this model. In AP/TD, longer surface durations in phrase-final and prominent positions result from Pi or MuT adjustments, which stretch gestural activation intervals in these positions. In recent versions of the model (Saltzman et al., 2008) this stretching is done by slowing the phonology-specific "clock," which is accomplished by slowing the oscillation frequency of an ensemble of gestural planning + suprasegmental oscillators. Because the duration of each gestural activation interval corresponds to a proportion of a planning oscillator period, slowing the gestural planning + suprasegmental ensemble of oscillators stretches the activation interval. Because this clock-slowing mechanism slows the phonology-specific clock without adding any extra timing units, intervals in phrase-final and prominent positions are not actually longer in phonology-specific clock time, even though they are longer in surface time.

These operational details and their implications are significant because they highlight the difficulty of accounting for greater timing variability for intervals that are longer in surface time but not in the number of phonology-specific timing units. That is, greater timing variability observed for longer surface duration intervals is straightforward to account for in a model where timing variability correlates with the number of timing units. AP/TD can use this type of account for the greater timing variability observed for longer duration phonemically long vowels as compared to shorter duration phonemically short vowels (cf. Figures 1 and 2 for examples of this variability pattern in N. Finnish and Dinka). This is because longer durations for phonemically long vowels correspond to greater numbers of phonology-specific timing units, e.g., phonemically long vowels are assumed to be composed of two gestures (or are potentially associated with two moras), with corresponding longer gestural activation intervals. However, AP/TD does not have an account for the greater timing variability for movements in phrase-final or phrasally prominent positions, since gestural activation intervals in these positions have the same number of AP/TD timing units as corresponding gestural activation intervals in phrase-medial, or non-prominent positions. This is because longer surface durations in these positions are due to AP/TD phonology-specific clock-slowing, rather than to a greater number of AP/TD phonology-specific clock units.

The number of phonology-specific timing units therefore is not a quantity that can be used to account for temporal variability within AP/TD. Neither is the degree of lengthening (i.e., of phonology-specific clock slowing as implemented through the height of a Pi or MuT gesture): Adding noise in proportion to Pi or MuT height might add timing variability of surface durations of long vowels, but would not explain the fact that phrase-medial unstressed vowels that are not accompanied by Pi or MuT gesture lengthening also show timing variability.

The findings instead argue for the representation of surface duration as a quantity, which is absent from AP/TD. In addition, AP/TD's reliance on phonology-specific timekeeping mechanisms provides no account of the similarity in timing variability behavior between speech and non-speech activity. This finding is more consistent with the use of noisy, general-purpose timekeeping mechanisms in both domains (e.g., Schöner, 2002 and many others). That is, in AP/TD, the fact that general-purpose timekeepers governing other motor behaviors, and the proposed phonology-intrinsic timekeeper, share the characteristic of greater variability for longer intervals goes unexplained.

# The Observation of Less Timing Variability at Goal-Related Parts of Movement

#### A Challenge to Spatio-Temporal Phonological Representations

These data are problematic for AP/TD because they suggest that actors are able to separately represent, and differentially prioritize, the timing of different components of movement, e.g., endpoints over other parts of movement, such as movement onset. These findings are difficult to explain in models such as

AP/TD, where a phonological representation takes the form of equations that, together with gestural activation, define the full trajectory of a gestural movement (as well as the trajectories of the individual movements of the articulators that form the gesture), once starting position has been specified. Thus, it is not possible to represent either the spatial or temporal aspects of one part of a movement (e.g., the endpoint) separately from the other parts of the movement trajectory. As a result, it is not possible to prioritize greater timing accuracy for different parts of a movement separately.

Note that the fact that the movement target is a parameter of movement in AP/TD does not mean that the target can be singled out as a part of movement that is independent of other parts. This is because the movement target parameter value, along with values for starting position, spring stiffness, mass, and damping parameters, affect the entire trajectory of movement, defined by the mass-spring equation, its activation, and overlap with other gestures.

It is important to note also, that even if a part of movement could be identified in this type of framework, there is nothing in the model that would predict different timing variability for a particular part of movement. For example, the timing of movement onset can be identified in this model as the onset of gestural activation. However, because the timing of all parts of movement is defined by the same equation of motion, and its gestural activation interval, there is no available mechanism to differentially prioritize any particular part of movement over another part for timing accuracy. And perhaps most importantly, because the entire movement trajectory (minus its starting position) represents the goal of movement, there is no principled reason for any part of movement to be prioritized for timing accuracy over any other part.

In sum, the evidence presents two challenges: The first, that individual parts of movement cannot be identified, is partially addressed in that movement onsets can be identified with the onset of gestural activation; however but crucially, movement endpoints cannot. The second challenge, that some parts of movement are more accurately timed than others, cannot be met because the equation of motion that describes the phonological representation defines the spatial and temporal properties of the entire gesture, apart from its starting position. Thus no part of it can vary independently of any other.

#### A Challenge to Onset-Based Movement Coordination

These findings also suggest that coordination patterns can be based on the part of movement most closely related to the phonological goal, often the movement endpoint, instead of the movement onset, as currently implemented in AP/TD. Whereas the movement onset corresponds to the onset of gestural activation, the movement endpoint is much more difficult to identify in this framework. This is because the time of gestural target approximation is determined primarily from properties of the gestural mass-spring, point-attractor oscillator, and only relates straightforwardly to the duration of an activation interval at a default speaking rate. That is, at a default speaking rate, gestural activation interval durations correspond to the planning oscillator phase proportion that gives each gesture enough time to approximate its target. However, when activation intervals are adjusted for different speaking rates, or for prominent, or boundary-adjacent position, the time of gestural approximation will no longer correspond to a fixed phase of a planning oscillator (e.g., the end of gestural activation). Specifically, if the gestural activation interval is longer than the time it takes for the gesture to approximate its target (because the planning oscillator system has been slowed, e.g., in boundary-adjacent position), then the end of gestural activation will not correspond to the point of target approximation, and will occur later. Put another way, the time of gestural target approximation cannot be identified as a particular phase of a gestural planning oscillator at speaking rates different from the default, and in prosodic contexts (e.g., boundary-adjacent positions, and phrasally prominent positions) where gestural activation intervals have been stretched. This is because in these contexts, gestural planning oscillator frequency (which determines how long gestures are active), is independent of the natural frequency of gestures themselves (which is invariant and determined by properties of the gestural point-attractor mass-spring system Byrd and Saltzman, 2003; Saltzman et al., 2008). Because it is the natural frequency of each gesture that is primarily responsible for the timing of target approximation (Saltzman and Munhall, 1989), it is challenging to identify a movement endpoint (or the time of target approximation) in the current AP/TD framework11. We note that tying gestural movement timing more closely to gestural activation timing (so that endpoints could be identified with a particular phase of a planning oscillator cycle) would present additional problems, e.g., overly long movement durations in contexts where gestural activation must be long (e.g., in phrasefinal positions or at slow speaking rates). For example, if a singer is asked to sing a single syllable /bA/ for a long period of time on a single note, s/he will typically move from a bilabial target to the vowel target relatively quickly, and then prolong the /A/ vowel by maintaining the oral tract in a quasi-"steady state," target position for the vowel. If the movement toward the vowel target is slowed down in proportion to the duration of the note, the speaker would end up producing what might sound like a continuum of vowel-like sounds between the release of [b] and the target for [A].

The findings presented above thus challenge the chosen architecture of AP/TD, with its spatio-temporal representations, lack of separation between Phonological and Phonetic Planning Components, phonology-intrinsic timing, and emergent (rather than explicitly represented) surface phonetic characteristics. We suggest that providing accounts of the phenomena described in earlier sections of the paper may be difficult without sacrificing some of the core principles of this theory's current implementation. For example, accounting for less timing variability at a part of movement most closely related to a goal challenges the core principle of an integrated phonologyphonetics, in which the phonological representation both serves as the goal of movement, and provides instructions

11Researchers working in the AP framework, e.g., Browman and Goldstein (1989, 1992), Davidson (2006), describe some patterns of observed data in terms of coordination patterns based on parts of movement other than the onset (e.g., target and release); however, they do not provide explicit mechanisms for identifying these parts of movement so they can be coordinated.

for implementing the movement. And the evidence for the representation of surface durations may be difficult to accommodate in such a system, without sacrificing spatiotemporal phonological representations and without having to translate from data structures in phonology to different data structures on the surface (in phonetics). The current system of adjusting gestural activation intervals in different contexts, while preserving the invariance of gestural representations, allowed the theory (1) to account for the phonological equivalence of the same gestures in different contexts, (2) to account for different (emergent) surface behavior of these gestures in different contexts, (3) to do both of these things without a separate Phonetic Planning Component that would provide translation from qualitatively different phonological representations to quantitatively specified surface phonetic forms. However, the findings presented in this paper suggest the need for just such a process, i.e., it suggests that the surface duration results of the adjustment processes are represented, and require translation from the data structures in phonology to those in phonetics.

# WHY THE FINDINGS POINT TOWARD A 3-COMPONENT MODEL BASED ON SYMBOLIC PHONOLOGICAL REPRESENTATIONS AND PHONOLOGY-EXTRINSIC TIMING

In this section, we argue that the findings presented above motivate the consideration of models of speech production with three components: (1) Phonological Planning, (2) Phonetic Planning, and (3) Motor-Sensory Implementation. Those findings provide a number of lines of evidence that support an approach of this kind, which is based on phonology-extrinsic timing and symbolic phonological representations. First, several findings suggested that surface durations are represented in the minds of speakers, and furthermore that these durations are specified through the use of non-speech-specific, generalpurpose mechanisms, in solar timing units. Because this evidence supports mechanisms for quantitative specification that are extrinsic to the phonology, it can easily be accommodated in a model of speech production in which quantitative specification occurs in a phonetic component that is separate from the symbol-based phonological plan (which does not contain specific spectral, spatial or temporal information) that the speaker develops for a particular utterance.

Further support for a model of speech motor control that has a separation between Phonological and Phonetic Planning Components is provided by findings of greater temporal accuracy at behaviorally meaningful parts of movement. These findings also motivate a third, Motor-Sensory Implementation Component that is separate from the two planning components, and is used for tracking and adjusting movements once they have begun. That is, the findings presented earlier can be explained if (1) a particular part of movement (e.g., the endpoint or possibly constriction release) is identified as "behaviorally meaningful," i.e., most closely related to the goals specified in the symbolic phonological plan (which is developed during the operation of a Phonological Planning Component) that the speaker is trying to signal, and (2) other aspects of the movement (specified during the operation of a Phonetic Planning Component) are organized in the service of reaching the behaviorally meaningful (and thus high-priority) part of movement at the right time, and with appropriate temporal and spatial accuracy. As a result, parts of movement that are less directly related to the goal are less likely to be corrected and adjusted during the operation of the Motor-Sensory Implementation Component, because their accuracy is less critical, as long as the goal-related part can be reached on time (cf. Todorov and Jordan, 2002, 2003, Minimal Intervention Principle). Instead, the resources for tracking and adjusting are focused on the aspects of a movement that are most closely related to the goal of producing a planned set of acoustic cues, e.g., its endpoint, or release from constriction.

To put this another way, in a three-component model that separates the phonological goal (as an abstract, symbolic, phonological element in an appropriate utterance-specific context) from the manner of carrying out the goal (as a quantitative phonetic specification that includes movement duration in solar timing units, e.g., ms)12, it is possible to relate the symbolic phonological goal to the part(s) of articulatory movement that are most closely related to achieving that phonological goal. Because those parts of movement have a separate representation from other parts, it is possible to prioritize them for temporal coordination, and for more accurate production in a motor-sensory implementation component. This is precisely what appears to be required by the distribution of timing accuracy across a movement. The identification of this part of a movement with the phonological goal of movement provides a rationale for why that particular part of movement should be given higher priority with regard to timing and/or spatial accuracy. In a three-component approach, the Motor-Sensory Implementation Component, which tracks timing and position relative to the endpoint (presumably based on prediction from an efference copy of the motor commands as well as on sensory information), is required to provide adjustments to the movements as they unfold, in order to ensure that the prioritized endpoint is reached at an appropriate time.

Several models in the literature are 3-component models, with separate Phonological Planning, Phonetic Planning, and Motor-Sensory-Implementation Components, and make use of surface durations, specified in solar timing units, and of phonology-extrinsic general-purpose timekeeping mechanisms (e.g., Fujimura, 1992 et seq., Guenther, 2016). These models are therefore promising, because they are compatible with many of the findings detailed above. However, in spite of their use of symbolic phonological representations, in some cases these models have identified the goals of movement as entire movements (Fujimura, 1992 et seq.), or as spectro-temporal trajectories (Guenther, 2016), as opposed to identifying the goals as particular parts of movement. These modeling decisions are at

12Note that phonological representations in our proposal can include discrete, relational and/or e.g. binary quantity representations, but not gradient, scalar representations.

odds with findings of greater timing accuracy at goal-related parts of movement. We suggest that if these models were modified to map phonological goals onto particular parts of movement, they would be compatible with the findings presented here. Lee's (1998) tau-coupling theory provides a way to account for less timing variability at goal-related parts of movement, because in that theory, movements are guaranteed to reach their goals at a particular time even if the timing of movement onset is variable. Lee's theory also provides a principled way to account for the time-course of movement (and resulting velocity profile shapes).

One challenge for any model of speech production, including 3-component models that use symbolic phonological representations and phonology-extrinsic timekeeping mechanisms, is to account for the systematic influence of a wide range of factors on timing patterns in speech. Optimal Control Theory approaches are promising in this regard, because they provide a way to balance the costs of not achieving movement goals (e.g., signaling phonemic contrast, in ways that are appropriate in particular prosodic positions, using a particular style, at an appropriate rate, etc.), with movement costs. See e.g., Šimko and Cummins (2010, 2011), Windmann et al. (2015), and Windmann (2016) for examples of ways that Optimal Control Theory approaches can be used to predict systematic timing patterns in speech. However, if these approaches are to be taken as theories of speech production, they present their own challenges; for example, they require extensive computation every time an utterance is planned.

# REFERENCES

In summary, evidence from the timing literature suggests that models of speech production based on symbolic representations and phonology-extrinsic timing are worth developing as alternatives to the currently dominant AP/TD approach, in spite of their computational challenges. See Turk and Shattuck-Hufnagel (2020) for a sketch of a specific proposal for how this might be done.

### AUTHOR CONTRIBUTIONS

AT synthesized and interpreted the evidence from the timing literature. AT and SS-H wrote the manuscript.

# FUNDING

This work was supported by AHRC Grant AH/1002758/1 to AT, and by U.S. National Science Foundation Grants BCS 1023596, 1651190, and 1827598 to SS-H.

# ACKNOWLEDGMENTS

We would like to thank Elliot Saltzman and Dave Lee for many theoretical discussions and explanations, as well as the editor and the two reviewers for valuable feedback. Any errors are ours.

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Turk and Shattuck-Hufnagel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Speech Sound Disorders in Children: An Articulatory Phonology Perspective

Aravind Kumar Namasivayam1,2 \*, Deirdre Coleman1,3, Aisling O'Dwyer1,4 and Pascal van Lieshout1,2,5

1 Oral Dynamics Laboratory, Department of Speech-Language Pathology, University of Toronto, Toronto, ON, Canada, 2 Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada, 3 Independent Researcher, Surrey, BC, Canada, 4 St. James's Hospital, Dublin, Ireland, 5 Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada

Speech Sound Disorders (SSDs) is a generic term used to describe a range of difficulties producing speech sounds in children (McLeod and Baker, 2017). The foundations of clinical assessment, classification and intervention for children with SSD have been heavily influenced by psycholinguistic theory and procedures, which largely posit a firm boundary between phonological processes and phonetics/articulation (Shriberg, 2010). Thus, in many current SSD classification systems the complex relationships between the etiology (distal), processing deficits (proximal) and the behavioral levels (speech symptoms) is under-specified (Terband et al., 2019a). It is critical to understand the complex interactions between these levels as they have implications for differential diagnosis and treatment planning (Terband et al., 2019a). There have been some theoretical attempts made towards understanding these interactions (e.g., McAllister Byun and Tessier, 2016) and characterizing speech patterns in children either solely as the product of speech motor performance limitations or purely as a consequence of phonological/grammatical competence has been challenged (Inkelas and Rose, 2007; McAllister Byun, 2012). In the present paper, we intend to reconcile the phonetic-phonology dichotomy and discuss the interconnectedness between these levels and the nature of SSDs using an alternative perspective based on the notion of an articulatory "gesture" within the broader concepts of the Articulatory Phonology model (AP; Browman and Goldstein, 1992). The articulatory "gesture" serves as a unit of phonological contrast and characterization of the resulting articulatory movements (Browman and Goldstein, 1992; van Lieshout and Goldstein, 2008). We present evidence supporting the notion of articulatory gestures at the level of speech production and as reflected in control processes in the brain and discuss how an articulatory "gesture"-based approach can account for articulatory behaviors in typical and disordered speech production (van Lieshout, 2004; Pouplier and van Lieshout, 2016). Specifically, we discuss how the AP model can provide an explanatory framework

#### Edited by:

Niels Janssen, University of La Laguna, Spain

#### Reviewed by: Wander M. Lowie,

University of Groningen, Netherlands Jonathan L. Preston, Syracuse University, United States

> \*Correspondence: Aravind Kumar Namasivayam<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Language Sciences, a section of the journal Frontiers in Psychology

Received: 28 April 2019 Accepted: 18 December 2019 Published: 28 January 2020

#### Citation:

Namasivayam AK, Coleman D, O'Dwyer A and van Lieshout P (2020) Speech Sound Disorders in Children: An Articulatory Phonology Perspective. Front. Psychol. 10:2998. doi: 10.3389/fpsyg.2019.02998

for understanding SSDs in children. Although other theories may be able to provide alternate explanations for some of the issues we will discuss, the AP framework in our view generates a unique scope that covers linguistic (phonology) and motor processes in a unified manner.

Keywords: speech sound disorders (SSD), Dynamical Systems Theory, Articulatory Phonology, childhood apraxia of speech (CAS), Dysarthria, articulation and phonological disorders, speech motor control, motor speech development

#### INTRODUCTION

In clinical speech-language pathology (S-LP), the distinction between articulation and phonology and whether a speech sound error1 arises from motor-based articulation issues or language/grammar based phonological issues has been debated for decades (see Shriberg, 2010; Dodd, 2014; Terband et al., 2019a for a comprehensive overview on this topic). The theoryneutral term Speech Sound Disorders (SSDs) is currently used as a compromise to bypass the constraints associated with the articulation versus phonological disorder dichotomy (Shriberg, 2010). The present definition describes SSD as a range of difficulties producing speech sounds in children that can be due to a variety of limitations related to perceptual, speech motor, or linguistic processes (or a combination) of known (e.g., Down syndrome, cleft lip and palate) and unknown origin (Shriberg et al., 2010; McLeod and Baker, 2017).

The history of causality research for childhood SSDs encompasses several theoretically motivated epochs (Shriberg, 2010). While the first epoch (1920s-1950s) was driven by psychosocial and structuralist views aimed at uncovering distal causes, the second epoch (1960s to 1980s) was driven by psycholinguistic and sociolinguistic approaches and focused on proximal causes. The more recent third and fourth epochs reflect the utilization of advances in neurolinguistics (1990s) and human genome sequencing (post-genomic era; 2000s) and these approaches address both distal and proximal causes (Shriberg, 2010). With these advances, several different systems for the classification of SSD subtypes in children have been proposed based on their distal or proximal cause (e.g., see Waring and Knight, 2013). Some of the major SSD classification systems include the Speech Disorders Classification System (Shriberg et al., 2010), the Model of Differential Diagnosis (Dodd, 2014) and the Stackhouse and Wells (1997) Psycholinguistic Framework. However, a critical problem in these classification systems as noted by Terband et al. (2019a) is that the relationships between the different levels of causation are underspecified. For example, the links between the etiology (distal; e.g., genetics), processing deficits (proximal; e.g., psycholinguistic factors), and the behavioral levels (speech symptoms) are not clearly elucidated. In other words, even though the term SSD is theory-neutral, the poorly specified links between the output level (behavioral) speech symptoms and higherlevel motor/language/lexical/grammar processes limits efficient differential diagnosis, customizing intervention and optimizing outcomes (see Terband et al., 2019a for a more detailed review on these issues). Thus, there is a critical need to understand the complex interactions between the different levels that ultimately cause the observable speech symptoms (McAllister Byun and Tessier, 2016; Terband et al., 2019a).

There have been several theoretical attempts at integrating phonetics and phonology in clinical S-LP. In this context, the characterization of speech patterns in children either solely as the product of performance limitations (i.e., challenges in meeting phonetic requirements arising from motor and anatomical differences) or purely as a consequence of phonological/grammatical competence has been challenged (Inkelas and Rose, 2007; Bernhardt et al., 2010; McAllister Byun, 2012). McAllister Byun (2011, 2012) and McAllister Byun and Tessier (2016) suggest a "phonetically grounded phonology" approach where individual-specific production experience and speech-motor development is integrated into the construction of children's phonological/grammatical representations. The authors discuss this approach using several examples related to the neutralization of speech sounds in word onset (with primary stress) positions. They argue that positional velar fronting in these positions (where coronals sounds are substituted for velar) in children is said to result from a combination of jaw-dominated undifferentiated tongue gesture (e.g., Gibbon and Wood, 2002; see Section "Speech Delay" for details on velar fronting and undifferentiated tongue gestures) and the child's subtle articulatory efforts (increased linguo-palatal contact into the coronal region) to replicate positional stress (Inkelas and Rose, 2007; McAllister Byun, 2012). McAllister Byun (2012) demonstrated that by encoding this difficulty with a discrete tongue movement as a violable "MOVE-AS-UNIT" constraint, positional velar fronting could be formally discussed within the Harmonic Grammar framework (Legendre et al., 1990). In such a framework the constraint inventory is dynamic and new constraints could be added on the basis of phonetic/speech motor requirements or removed over the course of neuro-motor maturation. In the case of positional velar fronting, the phonetically grounded "MOVE-AS-UNIT" constraint is eliminated from the grammar as the tongue-jaw complex matures (McAllister Byun, 2012; McAllister Byun and Tessier, 2016).

1The term "speech sound error" refers to a mismatch between what an individual intends to say and what they actually say (Harley, 2006). In children, this may entail a clinically significant impairment or a non-standard production of speech sounds of the ambient language and may be classified according to the units of processing (e.g., phoneme, syllable, word or phrase) and the mechanisms (substitutions, additions, omissions/deletions and distortions) involved (Harley, 2006; Preston et al., 2013). The word "sound" is included in the term "speech sound error" to distinguish it from other speech errors such as disfluencies, voice and language (e.g., grammatical errors) based errors (McLeod and Baker, 2017).

In the present paper, we intend to reconcile the phoneticphonology dichotomy and discuss the interconnectedness between these levels and the nature of SSDs using an alternative perspective. This alternative perspective is based on the notion of an articulatory "gesture" that serves as a unit of phonological contrast and characterization of the resulting articulatory movements (Browman and Goldstein, 1992; van Lieshout and Goldstein, 2008). We discuss articulatory gestures within the broader concepts of the Articulatory Phonology model (AP; Browman and Goldstein, 1992). We present evidence supporting the notion of articulatory gestures at the level of speech perception, speech production and as reflected in control processes in the brain and discuss how an articulatory "gesture"-based approach can account for articulatory behaviors in typical and disordered speech production (van Lieshout, 2004; van Lieshout et al., 2007; D'Ausilio et al., 2009; Pouplier and van Lieshout, 2016; Chartier et al., 2018). Although, other theoretical approaches (e.g., Inkelas and Rose, 2007; McAllister Byun, 2012; McAllister Byun and Tessier, 2016) are able to provide alternate explanations for some of the issues we will discuss, the AP framework in our view generates a unique scope that covers linguistic (phonology) and motor processes in a unified and transparent manner to generate empirically testable hypotheses. There are other speech production models, but as argued in a recent paper, the majority of those are more similar to the Task Dynamics (TD) framework (Saltzman and Munhall, 1989) in that they address specific issues related to the motor implementation stages (with or without feedback) and not so much include a principled account of phonological principles, such as formulated in AP (Parrell et al., 2019).

# ARTICULATORY PHONOLOGY

This section on Articulatory Phonology (AP; Browman and Goldstein, 1992) lays the foundation for understanding speech sound errors in children diagnosed with SSDs from this specific perspective. The origins of the AP model date back to the late 1970s, when researchers at the Haskins laboratories developed a unique and alternative perspective on the nature of action and representation called the Task Dynamics model (TD; Saltzman and Munhall, 1989). This model was inspired by concepts of selforganization related to functional synergies as derived from the Dynamical Systems Theory (DST; Kelso, 1995).

DST in general describes behavior as the emergent product of a "self organizing, multi-component system that evolves over time" (Perone and Simmering, 2017, p. 44). Various aspects of DST have been studied and applied in a diverse range of disciplines such as meteorology (e.g., Zeng et al., 1993), oceanography (e.g., Dijkstra, 2005), economics (e.g., Fuchs and Collier, 2007), and medical sciences (e.g., Qu et al., 2014). Recently, there has also been an uptake of DST informed research related to different areas in cognitive and speech-language sciences, including language acquisition and change (Cooper, 1999); language processing (Elman, 1995); development of cognition and action (Thelen and Smith, 1994; Spencer et al., 2011; Wallot and van Orden, 2011); language development (van Geert, 1995, 2008); 2nd language learning and development (de Bot et al., 2007; de Bot, 2008); speech production (see van Lieshout, 2004 for a review; van Lieshout and Neufeld, 2014; van Lieshout, 2017); variability in speech production (van Lieshout and Namasivayam, 2010; Jackson et al., 2016); connection between motor and language development (Parladé and Iverson, 2011); connection between cognitive aspects of phonology and articulatory movements (Tilsen, 2009); and visual word recognition (Rueckle, 2002); and visuospatial cognitive development (Perone and Simmering, 2017).

The role of DST in speech and language sciences, in particular with respect to speech disorders, is still somewhat underdeveloped, mainly because of the challenges related to applying specific DST analyses to the relatively short data series that can be collected in speech research (van Lieshout, 2004). However, we chose to focus on the AP framework, as it directly addresses issues related to phonology and articulation using DST principles related to relative stable patterns of behaviors (attractor states), that emerge when multiple components (neural, muscular, biomechanical) underlying these behaviors interact through time in a given context (self-organization) as shown in the time varying nature of the relationship between coupled structures (synergies) that express those behaviors (Saltzman and Munhall, 1989; Browman and Goldstein, 1992). Some examples of studies using this AP/DST approach can be found in papers on child-specific neutralizations in primary stress word positions (McAllister Byun, 2011), articulation issues related to /r/ production (van Lieshout et al., 2008), apraxia of speech (van Lieshout et al., 2007), studies on motor speech processes involved in stuttering (Saltzman, 1991; van Lieshout et al., 2004; Jackson et al., 2016), phonological development (Rvachew and Bernhardt, 2010), SSDs (Gildersleeve-Neumann and Goldstein, 2015), and in children with repaired cleftlip histories (van Lieshout et al., 2002). In the next few sections we will review the concept of synergies and the development of speech motor synergies, which are directly related to DST principles of self-organization and coupling, followed by how the AP model uses these concepts to discuss linguistic/phonological contrast.

## Speech Motor Synergies

The concept of speech motor synergy was derived from DST principles based on the notion that complex systems contain multiple (sub)components that are (functionally and/or physically) coupled (Kelso, 1995). This means that these (sub)components interact and function as a coordinated unit where patterns emerge and dissolve spontaneously based on selforganization, that is, without the need of a pre-specified motor plan (Turvey, 1990). These patterns are generated due to internal and external influences relating to inter-relationships between the (sub)components themselves, and the constraints and opportunities for action provided in the environment (Smith and Thelen, 2003). Constraints or specific boundary conditions that influence pattern emergence may relate to physical, physiological, and functional/task constraints (e.g., Diedrich and Warren, 1995; Kelso, 1995; van Lieshout and Namasivayam, 2010). Such principles of pattern formation and coupling have already been

demonstrated in physical (e.g., Gunzig et al., 2000) and biological systems (e.g., Haken, 1985), including neural network dynamics (e.g., Cessac and Samuelides, 2007). Haken et al. (1985), Kelso et al. (1985), and Turvey (1990) at the time were among the first to apply these principles also to movement coordination. Specifically, a synergy in the context of movement is defined as a functional assembly of (sub)components (e.g., neurons, muscles, joints) that are temporarily coupled or assembled in a taskspecific manner, thus constrained to act as a single coordinated unit (or a coordinative structure; Kelso, 1995; Kelso et al., 2009). In motor control literature, the concept of coordinative structures or functional synergies are typically modeled as (non-linear) oscillatory systems (Kelso, 1995; Newell et al., 2003; Profeta and Turvey, 2018). By strengthening or weakening the coupling within and between the system's interacting (sub)components, synergies may be tuned or altered. For movement control, the synergy tuning process occurs with development and learning or may change due to task demands or constraints (e.g., Smith and Thelen, 2003; Kelso et al., 2009).

With regards to speech production, perturbation paradigms similar to the ones used in other motor control studies have demonstrated critical features of oral articulatory synergies (e.g., Folkins and Abbs, 1975; Kelso and Tuller, 1983; van Lieshout and Neufeld, 2014), which in AP terms can be referred to as gestures. Functional synergies in speech production comprise of laryngeal and supra-laryngeal structures (tongue, lips, jaw) coupled to achieve a single constriction (location and degree) goal. Perturbing the movement of one structure will lead to compensatory changes in all functionally coupled structures (including the articulator that is perturbed) to achieve the synergistic goal (Kelso and Tuller, 1983). For example, when the jaw is perturbed in a downward direction during a bilabial stop closure, there is an immediate compensatory lowering of the upper lip and an increased compensatory elevation of the lower lip (Folkins and Abbs, 1975). The changes in the nature and stability of movement coordination patterns (i.e., within and between specific speech motor synergies) as they evolve through time can be captured quantitatively via order parameters such as relative phase. Relative phase values are expressed in degrees or radians, and the standard deviation of relative phase values can provide an index of the stability of the couplings (Kelso, 1995; van Lieshout, 2004). Whilst order parameters capture the relationship between the system's interacting (sub)components, changes in order parameter dynamics can be triggered by alterations in a set of control parameters. For example, changes in movement rate may destabilize an existing coordination pattern and result in a different coordination pattern as observed during gait changes (such as switching from a walk to a trot and then a gallop) as a function of required locomotion speed (Hoyt and Taylor, 1981; Kelso, 1995). For speech, such distinct behavioral patterns as a function of rate have not been established. However, in the coordination between lower jaw, upper and lower lip as part of a lip closing/opening synergy, typical speakers have shown a strong tendency for reduced covariance in the combined movement trajectory, despite individual variation in the actual sequence and timing of individual movements (Alfonso and van Lieshout, 1997). This can be considered a characteristic of an efficient synergy. The same study also included people who stutter and reported more instances of not showing reduced covariance in this group, in line with the notion that stuttering is related to limitations in speech motor skill (van Lieshout et al., 2004; Namasivayam and van Lieshout, 2011).

Recent work has provided more insights regarding cortical networks in control of this coordination between speech articulators (Bouchard et al., 2013; Chartier et al., 2018). Chartier et al. (2018) mapped acoustic and articulatory kinematic trajectories to neural electrode sites in brains of patients, as part of their clinical treatment of epilepsy. Similar to limb control studies that discovered single motor cortical neurons that encoded complex coordinated arm and hand movements (Aflalo and Graziano, 2006; Saleh et al., 2012), coordinated movements involving articulators for specific vocaltract configurations were encoded at the single electrode level in the ventral sensorimotor cortex (vSMC). That is, activity in the vSMC reflects the synergies used in speech production rather than individual movements. Interestingly, the study found four major clusters of articulatory kinematic trajectories that encode the main vocal tract configurations (labial, coronal, dorsal, and vocalic) necessary to broadly represent the production of American English sounds. The encoded articulatory kinematic trajectories exhibited damped oscillatory dynamics as inferred from articulatory velocity and displacement relationships (phase portraits). These findings support theories that envision vocal tract gestures as articulatory units of speech production characterized by damped oscillatory dynamics [Fowler et al., 1980; Browman and Goldstein, 1989; Saltzman and Munhall, 1989; see Section Articulatory Phonology and Speech Sound Disorders (SSD) in Children].

The notion of gestures at the level of speech perception has been discussed in the Theory of Direct Perception (Fowler, 1986; Fowler and Rosenblum, 1989). This theory posits that listeners perceive attributes of vocal tract gestures, arguing that this reflects the common code shared by both the speaker and listener (Fowler, 1986, 1996, 2014; Fowler and Rosenblum, 1989). These concepts are supported by a line of research studies which propose that the minimal objects of speech perception reflect gestures realized by the action of coordinative structures as transmitted by changes to the acoustic (and visual) signal, rather than units solely defined by a limited set of specific acoustic features (Diehl and Kluender, 1989; Fowler and Rosenblum, 1989; Fowler, 1996). The Direct Perception theory thus suggests that speech perception is driven by the structural global changes in external sensory signals that allow for direct recognition of the original (gesture) source and does not require special speech modules or the need to invoke the speech motor system (Fowler and Galantucci, 2005). Having a common unit for production and perception provides a useful framework to understand the broader nature of both sensory and motor involvement in speech disorders. For example, this can inform future studies to investigate how problems in processing acoustic information and thus perceiving the gestures from the speaker, may interfere with the tuning of gestures for production during development. Similarly, issues related to updating the state of the vocal tract through somato-sensory feedback (a critical component in

TD; Saltzman and Munhall, 1989; Parrell et al., 2019) during development may also lead to the mistuning of gestures in production, potentially leading to the type of errors in vocal tract constriction degree and/or location as discussed in Section "Articulatory Phonology and Speech Sound Disorders (SSD) in Children." However, for the current paper, the focus will be on production aspects only.

#### Development of Speech Motor Synergies

In this section, we will discuss the development and refinement of articulatory synergies and how these processes facilitate the emergence of speech sound contrasts. Observational and empirical data from several speech motor studies (as discussed below) were synthesized to create the timeline map of the development and refinement of speech motor control and articulatory synergies as illustrated in **Figure 1**. Articulatory synergies in infants have distinct developmental schedules. Speech production in infants is thought to be restricted to sounds primarily supported by the mandible (MacNeilage and Davis, 1990; Davis and MacNeilage, 1995; Green et al., 2000). Early mandibular movements (∼1 year or less) are ballistic in nature and restricted to closing and opening gestures due to the limited fine force control required for varied jaw heights (Locke, 1983; Kent, 1992; Green et al., 2000). Vowel productions in the first year are generally related to low, non-front, and non-rounded vowels; implying that the tongue barely elevates from the jaw, and there is limited facial muscle (lip) interaction (i.e., synergy) with the jaw (Buhr, 1980; Kent, 1992; Otomo and Stoel-Gammon, 1992; but see Giulivi et al., 2011; Diepstra et al., 2017).

Sound sequences that do not require complex timing and coordination within/between articulatory gestures are easier to produce and the first to emerge (Green et al., 2000; Green and Nip, 2010; **Figure 1**). For instance, young children are unable to coordinate laryngeal voicing gesture with supralaryngeal articulation and hence master voiced consonants and syllables earlier than voiceless ones (Kewley-Port and Preston, 1974; Grigos et al., 2005). The synergistic interaction between the laryngeal and supra-laryngeal structures underlying voicing contrasts is acquired closer to 2 years of age (∼20–23 months; Grigos et al., 2005), and follows the maturation of jaw movements (around 12–15 months of age; Green et al., 2002; **Figure 1**) and/or jaw stabilization (Yu et al., 2014).

In children, up to and around 2 years of age, there is limited fine motor control of jaw height (or jaw grading) and weak jawlip synergies during bilabial production, but relatively stronger inter-lip spatial and temporal coupling (Green et al., 2000, 2002; Nip et al., 2009; Green and Nip, 2010). A possible consequence of these interactions is that their production of vowels is limited to that of extremes (high or low; /i/, /u/, /o/, and /A/), and lip rounding/retraction is only present when the jaw is in a high position (Wellman et al., 1931; Kent, 1992; **Figure 1**). As speechrelated jaw-lip synergies are emerging, it is not surprising that children's ability to execute lip rounding and retraction is possible when degrees of freedom can be reduced (i.e., when jaw is held in a high position). Observation of such a reduction in degrees of freedom in emerging synergies has been observed in other non-speech systems (Bernstein, 1996). Interestingly, although the relatively strong inter-lip coordination pattern found in 2-yearolds is facilitative for bilabial productions, it needs to further differentiate to gain independent control of the functionally linked upper and lower lips prior to the emergence of labiodental fricatives (/f/ and /v/; Green et al., 2000; **Figure 1**). This process is observed to occur between the ages of 2 and 3 years (Stoel-Gammon, 1985; Green et al., 2000). Green et al. (2000, 2002) suggest that upper and lower lip movements become adult-like with increasing contribution of the lower-lip toward bilabial closure between the ages of 2 and 6 years. Further control over jaw height (with the addition of /ε/ and /O/) and lingual independence from the jaw is developed around 3 years of age (Kent, 1992). The latter is evident from the production of reliable lingual gliding movements (diphthongs: /aU/, /OI/, and /aI/) in the anterior-posterior dimension (Wellman et al., 1931; Kent, 1992; Otomo and Stoel-Gammon, 1992; Donegan, 2013). Control of this dimension also coincides with the emergence of coronal consonants (e.g., /t/ and /d/; Smit et al., 1990; Goldman and Fristoe, 2000). By 4 years of age, all front and back vowels are within the spoken repertoire of children, suggesting a greater degree of control over jaw height and improved tongue-jaw synergies (Kent, 1992). Intriguingly, front vowels and lingual coronal consonants emerge relatively late (Wellman et al., 1931; Kent, 1992; Otomo and Stoel-Gammon, 1992). This is possibly due to the fine adjustments required by the tongue tip and blade to adapt to mandibular angles. Since velar consonants and back vowels are produced by the tongue dorsum, they are closer to the origin of rotational movement (i.e., condylar axis) and are less affected than the front vowels and coronal consonants (Kent, 1992; Mooshammer et al., 2007). With maturation and experience, finer control over tongue musculature develops, and children begin to acquire rhotacized (retroflexed or bunched tongue) vowels (/Ç/ and /Ä/) and tense/lax contrasts (Kent, 1992).

The later development of refined tongue movements is not surprising, since the tongue is considered a hydrostatic organ with distinct functional segments (e.g., tongue tip, tongue body; Green and Wang, 2003; Noiray et al., 2013). Gaining motor control and coordinating the tongue with neighboring articulatory gestures is difficult (Kent, 1992; Smyth, 1992; Nittrouer, 1993). Cheng et al.'s (2007)study demonstrated a lower degree and more variable tongue tip to jaw temporal coupling in 6- to 7-year-old children relative to adults (**Figure 1**). This contrasts with the earlier developing lip-jaw synergy reported by Green et al. (2000), wherein by 6 years of age, children's temporal coupling of lip and jaw was similar to adults. The coordination of the tongue's subcomponents follows different maturation patterns. By 4–5 years, synergies that use the back of the tongue to assist the tongue tip during alveolar productions are adult-like (Noiray et al., 2013), while synergies relating to tongue tip release and tongue body backing are not fully mature (Nittrouer, 1993; **Figure 1**). The extent and variability of lingual vowel-on-consonant coarticulation between 6 and 9 years of age is greater than in adults; implying that children are still refining their tuning of articulatory gestures (Nittrouer, 1993; Nittrouer et al., 1996, 2005; Cheng et al., 2007; Zharkova et al., 2011).

SSD in Children: Articulatory Phonology Perspective

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These findings suggest that articulatory synergies have varying schedules of development: lip-jaw related synergies develop earlier than tongue-jaw or within tongue-related synergies (Cheng et al., 2007; Terband et al., 2009). Most of this work has been done on intra-gestural coordination (i.e., between individual articulators within a gesture), but it is clear that both the development of intra- and intergestural synergies are non-uniform and protracted (Whiteside et al., 2003; Smith and Zelaznik, 2004). Variability of intragestural synergies (e.g., upper- and lower-lip or lower lip– jaw) in 4- and 7-year-olds has been found to be greater than with adults but decreases with age until it plateaus between 7 and 12 years (Smith and Zelaznik, 2004). Adultlike patterns are reached at around 14 years, and likely continuously refine and stabilize even up to the age of 30 years (Smith and Zelaznik, 2004; Schötz et al., 2013; **Figure 1**). Overall, these findings suggest that the development of speech motor control is hierarchical, sequential, nonuniform, and protracted.

# Gestures, Synergies and Linguistic Contrast

As mentioned above, within the AP model, the fundamental units of speech are articulatory "gestures." Articulatory "gestures" are higher-level abstract specifications for the formation and release of task-specific, linguistically relevant vocal tract constrictions. The specific goals of each gesture are defined as Tract Variables (**Figure 2**) and relate to vocal tract constriction location (labial, dental, alveolar, postalveolar, palatal, velar, uvular, and pharyngeal) and constriction degree (closed, critical, narrow, mid, and wide; **Figure 2**). While constriction degree is akin to manner of production (e.g., fricatives /s/ and /z/ are assigned a "critical" value; stops /p/ and /b/ are given a "closed" value), constriction location allows for distinctions in place of articulation (Browman and Goldstein, 1992; Gafos, 2002).

The targets of each Tract Variable are implemented by specifying the lower-level functional synergy of individual articulators (e.g., articulator set of lip closure gesture: upper lip, lower lip, jaw) and their associated muscles ensembles (e.g., orbicularis oris, mentalis, risorius), which allows for the flexibility needed to achieve the task goal (Saltzman and Kelso, 1987; Browman and Goldstein, 1992; Alfonso and van Lieshout, 1997; Gafos, 2002; **Figure 2**). The coordinated actions of the articulators toward a particular value (target) of a Tract Variable is modeled using damped mass spring equations (Saltzman and Munhall, 1989). The variables in the equations specify the final position, the time constant of the constriction formation (i.e., the speed at which the constriction should be formed; stiffness), and a damping factor to prevent articulators from overshooting their targets (Kelso et al., 1986a,b; Browman and Goldstein, 1989; Saltzman and Munhall, 1989). For example, if the goal is to produce constriction at the lips (bilabial closure gesture), then the distance between the upper lip and lower lip (lip aperture) is set to zero. The resulting movements of individual articulators lead to changes in vocal tract geometry, with predictable aerodynamic and acoustic consequences.

The flexibility within the functional articulatory synergy implies that the task-level goals could be achieved with quantitatively different contributions from individual articulatory components as observed in response to articulatory perturbations or in adaptation to the linguistic context in which the gesture is produced (Saltzman and Kelso, 1987; Browman and Goldstein, 1992; Alfonso and van Lieshout, 1997; Gafos, 2002). In other words, the task-level goals are discrete, invariant or context-free, but the resulting articulatory motions are context-dependent (Browman and Goldstein, 1992). Gestures are phonological primitives that are used to achieve linguistic contrasts when combined into larger sequences (e.g., segments, words, phrases). The presence or absence of a gesture, or changes in gestural parameters like constriction location results in phonologically contrastive units. For example, the difference between "bad" and "ban" is the presence of a velum gesture in the latter, while "bad" and "pad" are differentiated by adding a glottal gesture for the onset of "bad". Parameter differences in gestures such as the degree of vocal tract constriction yields phonological contrast by altering manner of production (e.g., "but" and "bus"; tongue tip constriction degree: complete closure for /t/ vs. a critical opening value to result in turbulence for /s/) (Browman and Goldstein, 1986, 1992; van Lieshout et al., 2008).

Gestures have an internal temporal structure characterized by landmarks (e.g., onset, target, release) which can be aligned to form segments, words, sentences and so on (Gafos, 2002). These gestures and their timing relationships are represented by a gestural score in the AP model (**Figure 2**; Browman and Goldstein, 1992). Gestural scores are estimated from articulatory kinematic data or speech acoustics by locating kinematic/acoustic landmarks to determine the timing relationships between gestures (Nam et al., 2012). The timing relationships in the gestural score are typically expressed as relative phase values (Kelso et al., 1986a,b; van Lieshout, 2004). Words may differ by altering the relative phasing between their component gestures. For example, although the gestures are identical in "pat" and "tap," the relative phasing between the gestures are different (Saltzman and Byrd, 2000; Saltzman et al., 2006; Goldstein et al., 2007). As mentioned above, the coordination between individual gestures in a sequence is referred to as intergestural coupling/coordination (van Lieshout and Goldstein, 2008). Inter-gestural level timing is not rigidly specified across an entire utterance but is sensitive to peripheral (articulatory) events (Saltzman et al., 1998; Namasivayam et al., 2009; Tilsen, 2009). The presence of a coupling between inter-gestural level timing oscillators and feedback signals arising from the peripheral articulators was identified in experimental work by Saltzman et al. (1998). In that study, unanticipated lip perturbation during discrete and repetitive production of the syllable /pa/ resulted in phase-shifts in the relative timing between the two independent gestures (lip closure and laryngeal closure) for the phoneme /p/ and between successive /pa/ syllables (Saltzman et al., 1998). This confirms the critical role of somato-sensory information in the TD model (Saltzman and Munhall, 1989; Parrell et al., 2019).

Dynamical systems can express different self-organizing coordination patterns, but for many systems, certain patterns of coordination seem to be preferred over others. These preferred

patterns are induced by "attractors" (Kelso, 1995), which reflect stable states in the coupling dynamics of such a system2 . The coupling relationships used in speech production are similar to those identified for limb control systems (Kelso, 1995; Goldstein et al., 2006) and capitalize on intrinsically stable modes of coordination (specifically, in-phase and anti-phase modes; Haken et al., 1985). These are patterns that are naturally achieved without training or learning; however, they are not equally stable (Haken et al., 1985; Nam et al., 2009). In-phase coordination patterns, for instance, are relatively more stable than anti-phase patterns (Haken et al., 1985; Kelso, 1995; Goldstein et al., 2006). Other coordination patterns are possible, but they are more variable, may require higher energy expenditure and can only be acquired with significant training (Kelso, 1984; Peper et al., 1995; Peper and Beek, 1998; Nam et al., 2009). For example, when participants are asked to oscillate two limbs or fingers, they spontaneously switch coordination patterns from the less stable anti-phase to the more stable in-phase as the required movement frequency increases, but not vice versa (Kelso, 1984; Haken et al., 1985; Peper et al., 2004). These two modes of coordination likely form the basis of syllable structure (Goldstein et al., 2006). The onset consonant (C) and vowel (V) planning oscillators (see below) are said to be coupled in-phase, while the CC onset clusters and the nucleus (V) and coda (C) gestures are coupled in anti-phase mode. As the in-phase coupling mode is more stable, this can explain the dominance of CV syllable structure during babbling and speech development as well as across languages (Goldstein et al., 2006; Nam et al., 2009; Giulivi et al., 2011).

Using the TD framework in the AP model (Nam and Saltzman, 2003), speech production planning processes and dynamic multifrequency coupling between gestural and rhythmic (prosodic) systems have been explained using the notion of coupled oscillator models (Goldstein et al., 2006; Nam et al., 2009; Tilsen, 2009; Gafos and Goldstein, 2012). The coupled oscillator models for speech gestures are associated with non-linear (limit cycle)

2There are also certain states that are inherently unstable, which are referred to as repellors.

planning level oscillators which can be coordinated in relative time by specifying a phase relationship between them. During an utterance, the planning oscillators for multiple gestures generate a representation of the various (and potentially competing) coupling specifications, referred to as a coupling graph (**Figure 2**; Saltzman et al., 2006). The activation of each gesture is then triggered by its respective oscillator after they settle into a stable pattern of relative phasing during the planning process (van Lieshout and Goldstein, 2008; Nam et al., 2009). In this manner, the coupled oscillator model has been used to control the relative timing of multiple gestural activations during word or sentence production. To recap, individual gestures are modeled as critically damped mass-spring systems with a fixed-point attractor where speed, amplitude and duration are manipulated by adjustments to dynamic parameter specifications (e.g., damping and stiffness variables). In contrast, gestural planning level systems are modeled using limit cycle oscillators and their relative phases are controlled by potential functions (Tilsen, 2009; Pouplier and Goldstein, 2010).

Similar to the bidirectional relationship between inter-gestural timing and peripheral articulatory state, interactions between gestural and rhythmic level oscillators have also been noted. To explain the dynamic interactions between gestural and rhythmic (stress and prosody) systems, speech production may rely on a similar multi-frequency system of coupled oscillators as proposed for limb movements (Peper et al., 1995; Tilsen, 2009). The coupling strength and stability in such systems varies not only as a function of type of phasing (in-phase or anti-phase), but also by the complexity of coupling (ratio of intrinsic oscillator frequencies of the coupled structures), movement amplitude and the movement rate at which the coupling needs to be maintained (Peper et al., 1995; Peper and Beek, 1998; van Lieshout and Goldstein, 2008; van Lieshout, 2017). For example, rhythmic movement between the limbs has been modeled as a system of coupled oscillators that exhibit (multi)frequency locking. The most stable coupling mode is when two or more structures (oscillators) are frequency locked in a lower-order (e.g., 1:1) ratio. Multi-frequency locking for upper limbs is possible at higher order ratios of 3:5 or 5:2 (e.g., during complex drumming) but only at slower movement frequencies. As the required movement rate increases, the complex frequency coupling ratios will exhibit transitions to simpler and inherently more stable ratios (Peper et al., 1995; Haken et al., 1996). Studies on rhythmic limb coupling show that increases in movement frequency are inversely related to decreases in coupling strength and coordination stability. The increases in movement frequency or rate may be associated with a drop in the movement amplitude that mediates the differential loss of stability across the frequency ratios (Haken et al., 1996; Goldstein et al., 2007; van Lieshout, 2017). However, smaller movement amplitude in itself (independent from duration and rate) can also decrease coupling strength and coordination stability (Haken et al., 1985; Peper et al., 2008; van Lieshout, 2017). Amplitude changes are presumably used to stabilize the output of a coupled neural oscillatory system. Smaller movement amplitudes may decrease feedback gain, resulting in a reduction of the neural oscillatoreffector coupling strength and stability (Peper and Beek, 1998; Williamson, 1998; van Lieshout et al., 2004; van Lieshout, 2017). Larger movement amplitudes facilitate neural phase entrainment by enhancing feedback signals, but a certain minimum sensory input is required for entrainment to occur (Williamson, 1998; Ridderikhoff et al., 2005; Peper et al., 2008; Kandel, 2013; van Lieshout, 2017). Several studies have demonstrated the critical role of movement amplitude on coordination stability in different types of speech disorders such as stuttering and apraxia (van Lieshout et al., 2007; Namasivayam et al., 2009; for review see Namasivayam and van Lieshout, 2011).

Such complex couplings between multi-frequency oscillators may be found at different levels in the speech system such as between slower vowel production and faster consonantal movements (Goldstein et al., 2007), or between shorter-time scale gestures and longer-time scale rhythmic units (moras, syllables, feet and phonological phrases; Tilsen, 2009). Experimentally, the interaction between gestural and rhythmic systems have been identified by a high correlation between inter-gestural temporal variability and rhythmic variability (Tilsen, 2009), while behaviorally, such gesture-rhythm interactions are supported by observations of systematic relationships between patterns of segment and syllable deletions, and stress patterns in a language (Kehoe, 2001; for an alternative take on neutralization in strong positions using constraint-based theory and AP model see McAllister Byun, 2011). Issues in maintaining the stability of complex higher order ratios in multi-frequency couplings (especially at faster speech rates) between slower vowel production and faster consonantal movements have also been implicated in the occurrence of speech sound errors in healthy adult speakers (Goldstein et al., 2007). More about this aspect in the next section.

The development of gestures is tied to organs of constriction in two ways: between-organ and within-organ differentiation (Goldstein and Fowler, 2003). There is empirical data to support that these differentiations occur over developmental timelines (Cheng et al., 2007; Terband et al., 2009; see Section Development of Speech Motor Synergies). When a gesture corresponds to different organs (e.g., bilabial closure implemented via upper and lower lip plus jaw), betweenorgan differentiation is observed at an earlier stage in development. For within-organ differentiation, children must learn that for a given organ, different gestures may require different variations in vocal tract constriction location and degree. For example, /d/ and /k/ are produced by the same constriction organ (tongue) but use different constriction locations (alveolar vs. velar). Within-organ differentiation is said to occur at a later stage in development via a process called attunement (Studdert-Kennedy and Goldstein, 2003). During the attunement process, initial speech gestures produced by an infant (i.e., based on between organ contrasts) become tailored (attuned) toward the perceived finer grained differentiations in gestural patterns in the ambient language (e.g., similar to phonological attunement proposed by Shriberg et al., 2005). In sum, gestural planning, temporal organization of gestures, parameter specification of gestures, and gestural coupling (between gestures, and between gestures and other rhythmic units) result in specific behavioral phenomena including casual

speech alternations (e.g., syllable deletions, assimilations), as will be discussed next.

# Describing Casual Speech Alternations

The AP model accounts for variations and errors in the speech output by demonstrating how the task-specific gestures at the macroscopic level are related to the systematic changes at the microscopic level of articulatory trajectories and resulting speech acoustics (e.g., speech variability, coarticulation, allophonic variation, and speech errors in casual connected speech; Saltzman and Munhall, 1989; Browman and Goldstein, 1992; Goldstein et al., 2007). Browman and Goldstein (1990b) argue that speech sound errors such as consonant deletions, assimilations, and schwa deletions can result from an increasing overlap between different gestures, or from reducing the size (magnitude) of articulatory gestures (see also van Lieshout and Goldstein, 2008; Hall, 2010). The amount of gestural overlap is assumed to be a function of different factors, including style (casual vs. formal speech), the organs used for making the constrictions, speech rate, and linguistic constraints (Goldstein and Fowler, 2003; van Lieshout and Goldstein, 2008).

The gestural processes surrounding consonant and schwa deletions can be explained by alterations in gestural overlap resulting from changes in relative timing or phasing in the gestural score. The gestural overlap has different consequences in the articulatory and acoustic output, depending on whether the gestures share the same Tract Variables and corresponding articulatory sets (homorganic) or whether they employ different Tract Variables and constricting organs (heterorganic). Heterorganic gestures (e.g., lip closure combined with a tongue tip closure) will result in a Tract Variable motion for each gesture that is unaffected by the other concurrent gesture; and their Tract Variables goals will be reached, regardless of the degree of overlap. However, when maximum overlap occurs, one gesture may completely obscure or hide the other gesture acoustically during release (i.e., gestural hiding; Browman and Goldstein, 1990b). In homorganic gestures, when two gestures share the same Tract Variables and articulators, as in the case of a tongue tip (TT) constriction to produce /θ/ and /n/ (e.g., during production of /tεn θimz/) they perturb each other's Tract Variable motions. The dynamical parameters of the two overlapping gestural control regimes are 'blended.' These gestural blendings are traditionally described phonologically as assimilation (e.g., /tεn θimz/ → [tε θimz]) or allophonic variations (e.g., front and back variation of /k/ in English: "key" and "caw"; Ladefoged, 1982) (Browman and Goldstein, 1990a,b).

Articulatory kinematic data collected using an X-Ray Microbeam system (e.g., Browman and Goldstein, 1990b) have provided support for the occurrence of these gestural processes (hiding and blending). Consider the following classic examples in the literature (Browman and Goldstein, 1990b). The production of the sequence "nabbed most" is usually heard by the listener as "nab most" and the spectrographic display reveals no visible presence of /d/. However, the presence of the tongue tip raising gesture for /d/ can be seen in X-ray data (Browman and Goldstein, 1990b), but it is inaudible and completely overlapped by the release of the bilabial gestures /b/ and /m/ (Hall, 2010). Similarly, in fast speech, words like "potential" sound like "ptential," wherein the first schwa between the consonants /p/ and /t/ seems to be omitted, but in fact is hidden by the acoustic release of /p/ and /t/ (Byrd and Tan, 1996; Davidson, 2006; Hall, 2010). These cases show that relevant constrictions are formed, but they are acoustically and perceptually hidden by another overlapping gesture (Browman and Goldstein, 1990b). Assimilations have also been explained by gestural overlap and gesture magnitude reduction. In the production of "seven plus seven," which often sounds like "sevem plus seven," the coronal nasal consonant /n/ appears to be replaced by the bilabial nasal /m/ in the presence of the adjacent bilabial /p/. In reality, the tongue tip /n/ gesture is reduced in magnitude and overlapped by the following bilabial gesture /p/ (Browman and Goldstein, 1990b; Hall, 2010). The AP model accounts for rate-dependent speech sound errors by gestural overlap and gestural magnitude reduction (Browman and Goldstein, 1990b; Hall, 2010). Auditory-perceptual based transcription procedures would describe the schwa elision and consonant deletion (or assimilation processes) in the above examples by a set of phonological rules schematically represented as d → ∅/C\_C (i.e., /d/ is deleted in the presence of two adjacent consonants in "nabbed most" → "nab most"; Hall, 2010). However, these rules do not capture the fact that movements for the /d/ or /n/ are still present. Furthermore, articulatory data indicate that such speech sound errors are often not the result of whole-segment or feature substitutions/deletions, but are due to co-production of unintended or intrusion gestures to maintain the dynamic stability in the speech production system instead (Pouplier and Goldstein, 2005; Goldstein et al., 2007; Pouplier, 2007, 2008; Slis and van Lieshout, 2016a,b).

The concept of intrusion gestures is illustrated with kinematic data from Goldstein et al. (2007) study where participants repeated bisyllabic sequences such as "cop top" at fast and slow speech rate conditions. Goldstein et al. (2007) noticed unique speech sound errors in that both the intended and extra/unintended (intruding) gestures were produced at the same time. True substitutions and deletions of the targets occurred rarely, even though, substitution errors are the most commonly reported error type in speech sound error studies when using auditory-perceptual transcription procedures (Dell et al., 2000). Goldstein et al. (2007) explained their findings based on the DST concepts of stable rhythmic synchronization and multi-frequency locking (see Section Gestures, Synergies and Linguistic Contrast). The word pairs "cop top" differ in their onset consonant but share the syllable rhyme. Thus, each production of "cop top" contains one tongue tip (/t/), one tongue dorsum (/k/) gesture, but two labial (/p/) gestures. This results in the initial consonants being in a 1:2 relationship with the coda consonant. Such multifrequency ratios are intrinsically less stable (Haken et al., 1996), especially under fast rate conditions. As speech rate increased, they observed an extra copy of tongue tip inserted or coproduced during the /k/ production in "cop" and a tongue dorsum intrusion gesture during the /t/ production in "top." Adding an extra gesture (the intrusion) results in a more stable harmonic relationship where both the initial consonants (tongue tip and tongue dorsum gestures) are in a 2:2 (or 1:1) relationship

with the coda (lip gestures) consonant (Pouplier, 2008; Slis and van Lieshout, 2016a,b). Thus, gestural intrusion errors can be described as resulting from a rhythmic synchronization process, where the more complex and less stable 1:2 frequency-locked coordination mode is dissolved and replaced by a simpler and intrinsically more stable 1:1 mode by adding gestures. Unlike what is claimed for perception-based speech sound errors (e.g., Dell et al., 2000), the addition of "extra" cycles of the tongue tip and/or tongue dorsum oscillators results in phonotactically illegal simultaneous articulation of /t/ and /k/ (Goldstein et al., 2007; Pouplier, 2008; van Lieshout and Goldstein, 2008; Slis and van Lieshout, 2016a,b). The fact that /kt/ co-production is phonotactically illegal in English makes it difficult for a listener to even detect its presence. Pouplier and Goldstein (2005) further suggest that listeners only perceive intrusions that are large in magnitude (frequently transcribed as segmental substitutions errors), while smaller gestural intrusions are not heard, and targets are scored as error-free despite conflicting articulatory data (Pouplier and Goldstein, 2005; Goldstein et al., 2007; see also Mowrey and MacKay, 1990).

# ARTICULATORY PHONOLOGY AND SPEECH SOUND DISORDERS (SSD) IN CHILDREN