Studies were screened by independent reviewers and Cohen ’s kappa measured inter-coder agreement . Results The database search retrieved 1513 citations ; 17 articles ( 14 different conversational agents ) met the inclusion criteria . Dialogue management strategies were mostly finite-state and frame-based ( 6 and 7 conversational agents , respectively ) ; agent-based strategies were present in one type of system . To obtain student candidate satisfaction apart from the quality of education must also be accompanied by providing consultation services and information to them . This paper proposes the development of Chatbot which acts as a conversation agent that can play a role of as student candidate service . This Chatbot is called Dinus Intelligent Assistance ( DINA ) . In this paper we describe a conversational virtual agent that is designed to be used in conjunction with group medical visits to help treat individuals with chronic pain and depression using non-medical treatments including yoga , meditation , and self-massage . Results from two rounds of pilot testing indicate that patients like the virtual agent and find that it helps them manage their condition . People fundamentally questioned the need for bond and common ground in agent communication , shifting to more utilitarian definitions of conversational qualities . Drawing on these findings we discuss key challenges for conversational agent design , most notably the need to redefine the design parameters for conversational agent interaction . Third , the Expression of Empathy by which EMMA ’s multiple modalities are triggered through the modulated empathic emotion . The proposed model of empathy is illustrated in a conversational agent scenario involving the virtual humans MAX and EMMA . The human and machine users of the system have the ability to add , remove , or edit existing information using the CNL , including extensions to the model ( or schema ) in real-time . In this paper we describe various examples undertaken using this approach along with initial experiments using a conversational software agent to enable the field user to interact with such information in full natural English language . Loneliness and social isolation are significant problems in older adult populations . We describe a conversational agent-based system designed to provide longitudinal social support to isolated older adults . Results from an exploratory pilot study indicate that when the agent proactively draws elders into interactions , it is more effective at addressing loneliness than when the agent passively relies upon elders to initiate interactions . Cultural differences in humans bargaining behavior are the focus of this study . We investigate the dynamics of human game playing with a conversational computational agent ( Virtual Human ) . We demonstrate that the cultural background influences their observed behavior in this task . Upon entering the Lobby , they are matched with other students that are logged in to it . Once matched , they are provided with a link to a chat room where they can work with their partner students on a synchronous collaboration activity , supported by a conversational computer agent . Results of a survival model in which we control for level of effort suggest that having experienced a collaborative chat is associated with a slow down in the rate of attrition over time by a factor of two . marino2016more explicitly incorporate knowledge graphs into an image classification model . Xu2016 created a recall mechanism into a standard LSTM cell that retrieves pieces of external knowledge encoded by a single representation for a conversation model . Concurrently , Dhingra2017 exploit linguistic knowledge using MAGE - GRUs , an adapation of GRUs to handle graphs , however , external knowledge has to be present in form of triples . Insights from a Comparative Analysis . A chatbot is a software that is able to autonomously communicate with a human being through text and due to its usefulness , an increasing number of businesses are implementing such tools in order to provide timely communication to their clients . In the past , whilst literature has focused on implementing innovative chatbots and the evaluation of such tools , limited studies have been done to critically comparing such conversational systems . Multiple frameworks have been developed to ease their definition and deployment . While these frameworks are efficient to design simple chatbot applications , they still require advanced technical knowledge to define complex interactions and are difficult to evolve along with the company needs ( e.g. it is typically impossible to change the NL engine provider ) . In addition , the deployment of a chatbot application usually requires a deep understanding of the targeted platforms , especially back-end connections , increasing the development and maintenance costs . The ensemble model used in this project resulted in a accuracy of 67 % with MFCC features which is the highest when compared to other models . After successful identification of emotions , a chatbot framework is presented which can adapt to interactive dialogues with the customer based on the emotion from the speech in the audio . In addition to this , the results of the previous related work and research gaps are discussed . But with the recent AI developments , like neural networks and natural language processing , companies like Google , Amazon , or IBM , offers coding-free platforms that can enable a non-technical person to create a chatbot that can fit into their own needs . Using these chatbot platforms , The University of Hong Kong ( HKU ) , through Technology-Enriched Learning Initiative , leverages on its experiences in integrating this technology to better enhance the learning experience of the students . In this workshop , we would like to share our experience gained from developing a set of chatbots for an online blended learning environment . Nevertheless chatbots are widespread in several applications , especially to provide information to users in a new and enjoyable way . In this chapter we describe different chatbot architectures , exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots : the knowledge base building and the rigidness of the dialogue mechanism . We will do so in a progressive manner and will make the chatbot in two layers . The first section of the chapter introduces the chatbot concept , followed by a section on implementing a basic rule-based chatbot system . The last section discusses the training of a sequence-to-sequence ( seq2seq ) recurrent neural network ( RNN ) model on a publicly available dataset . Based on the literature review of intelligent tutoring systems for English instruction and the demand analysis for English instruction in China , and under the guideline of learning theories , such as behaviorism , constructivism and situated learning theory , we have been kept on designing and developing CSIEC intelligent English tutoring system to facilitate the teaching and learning of English in China . Besides the original chatbot function for dialogue simulation , we have developed intelligent vocabulary assessment function and course management function . Last but not least , we deploy our transfer learning model for PI into our online chatbot system , which can bring in significant improvements over our existing system . Finally , we launch our new system on the chatbot platform Eva in our E-commerce site AliExpress . Recurrent Neural Network based Sequence-to-sequence ( Seq2Seq ) model is one of the most commonly researched model to implement artificial intelli-gence chatbot and has shown great progress since its introduction in 2014 . However , it is still in infancy and has not been applied widely in educational chatbot development . Introduced originally for neural machine translation , the Seq2Seq model has been adapted for conversation modelling including question-answering chatbots . Chatbot market can be divided into five regions : North America , Europe , Asia Pacific , Latin America and MEA . Raiffeisen bank implemented the first enterprise chatbot solution in Serbia . REA ( Raiffeisen Electronic Assistant ) is a chatbot built on Weaver platform . We also discussed the various data sources that are available in designing an enterprise chatbot . There are many chatbot builder platforms and frameworks available in the market that can be used to build chatbots . These frameworks abstract much complex functionality and provide components that are reusable , extendable , and scalable . The typology dimensions address key characteristics that differentiate current chatbots : the duration of the user ’s relation with the chatbot ( short-term and long-term ) , and the locus of control for user ’s interaction with the chatbot ( user-driven and chatbot-driven ) . To explore the usefulness of the typology , we present four example chatbot purposes for which the typology may support analysis of high-level chatbot interaction design . Furthermore , we analyse a sample of 57 chatbots according to the typology dimensions . A chatbot is a computer program which can interact with humans through natural language . In this paper , we introduced Jiao Xiao Tong , an interactive question answering chatbot designed in assisting students and faculties in Shanghai Jiao Tong University to accomplish various campus activities such as setting remainders , answering school trivia questions , route navigation and etc . A two-part experiment was conducted to evaluate two aspects of chatbot user experience . We present a number of solutions and describe the different components of the BOTTA chatbot . The BOTTA database files are publicly available for researchers working on Arabic chatbot technologies . The BOTTA chatbot is also publicly available for any users who want to chat with it online . The results were derived on base of an online survey among the solution providers . It turned out that a high percentage of the functionalities , which are decisive for a valuable entrepreneurial chatbot application , are covered by the providers , however , with nuanced differences being observed regarding particular features . The intelligent chat-bot tool will be available 24 hours a day at schools or public libraries or any other location which has internet access . The intelligent chatbot tool will make use of Natural Language Processing techniques to answer the queries by high school students . The intelligent chat-bot tool will be trained on a knowledge base comprising of general knowledge questions and answers . The renewal of this research is to add access to subject matter features and discussion forum features . These features do not yet exist in the chatbot application system in other studies . Authentication on the chatbot is needed to find out who the user is accessing the chatbot for the material , discussion forum , and work on the problem training and National Examination exercises . Compared with naive rule-based approaches , our chatbot trained via the PA4C model avoids hand-crafted action selection and is more robust to user utterance variance . The PA4C model optimizes conventional RL models with action parameterization and auxiliary tasks for chatbot training , which address the problems of a large action space and zero-reward states . We evaluate the PA4C model over training a chatbot for calendar event creation tasks . Focused on the three subprocesses in the chatbot architecture : text processing , semantic understanding , and response generation . Moreover , the survey is conducted with classification of chatbot evaluation methods and their analysis according to chatbot types and three main evaluation schemes ; content evaluation , user satisfaction , and chat function . This paper introduces a potential solution to provide them with what they are seeking for- a chatbot . The proposed chatbot is a cancer chatbot designed only for people dealing with cancer . People can ask about anything and everything about cancer- symptoms , treatments , survival and so on . For instance , in the application of machine translation , a task specific sequence score / loss , bilingual evaluation understudy ( BLEU ) , can be adopted to guide the sequence generation . However , in many other practical applications , such as poem generation and chatbot , a task specific loss may not be directly available to score a generated sequence accurately . General adversarial net ( GAN ) proposed by is a promising framework for alleviating the above problem . subsection : Interaction Layer Interaction mechanism is widely used in tasks of matching source and target textual contents , such as natural language inference and retrieve - based chatbot . The key idea of interaction mechanism is to use the interaction features between the small units ( e.g. , words in the textual contents ) to infer fine - grained clues whether two contents are matching . The study includes the task analysis of some of the user 's specific needs in everyday life , the problems faced by the user while trying to do them , a brief description of the workarounds and their degree of usability in terms of efficiency and satisfaction . While the combination of VoiceOver and Siri gives the user some degree of accessibility , the most notorious access problems were the difficulty to do manual gestures involving more than one finger , and editing text with the keyboard . Besides the obvious need to continue analyzing voice and manual interaction modes , it is required the exploration of other gesture controls on the device , or the use of alternative gadgets in order to improve the mobile accessibility of people with multiple disabilities . Bots , Virtual Assistants and Virtual Agents are well known in a personal environment . Technologies like “ Apple Siri ” or “ Amazon Alexa ” serve as digital assistants to enhance both accessibility and productivity . Yet , these technologies have to play with different rules in the enterprise context . This paper formulates two stochastic nonautonomous SIRI epidemic systems with nonlinear perturbations . The main aim of this study is to investigate stochastic dynamics of the two SIRI epidemic systems and obtain their thresholds . For the nonautonomous stochastic SIRI epidemic system with white noise , the authors provide analytic results regarding the stochastic boundedness , stochastic permanence and persistence in mean . Moreover , the authors prove that the system has at least one nontrivial positive T-periodic solution by using Lyapunov function and Hasminskii ’s theory . The method used in this research proposed three tasks and usability was investigated from the performance analysis based on time and perceptions of the volunteers through questionnaires . Age was found not to be the only factor influencing the usability of the Siri virtual assistant . Other factors , such as prior knowledge , education level and personal motivation , are capable of influencing the research results of usability criteria . The results also demonstrate that information service providers should always offer mobile-friendly interfaces ( i.e. , RESTful web services with JSON encoding ) when possible . The benchmarking software is made available as an open-source application so that others can perform their own experiments , and so that app developers can use this library as a foundation for building new applications based on the SIRI format . Steve Muskal of Eidogen-Sertanty [ 3 ] remarks on the power of voice recognition : Siri can achieve greater than 90 % accuracy even with science terms . Amazon has a Siri-like device [ 4 ] which does far field listening . Muskal adds that he can capture and analyze audio with a recording app ( RecordUp ) that detects breaks , and uploads segments to Dropbox . The purpose of this study was to investigate the importance of intelligent personal assistants ' speech for the user experience and if it increases with more naturalness . The intelligent personal assistant Siri was chosen to perform an experiment with repeated measures design consisting of three levels : Siri 's speech , natural speech mimicking Siri 's prosody and natural speech . The results revealed no statistically significant difference between the three levels . INVESTIGATING SIRI AS A VIRTUAL ASSISTANT IN A LEARNING CONTEXT ? . In this paper , we address challenges arising from the use of the conversational interface Siri during a literacy activity in a learning context . On one hand , we investigate potentialities of Siri as a virtual assistant and knowledge navigator for task accomplishment . Task oriented dialogue systems can reduce operating costs by automating processes such as call center dispatch and online customer support . Moreover , when combined with automatic speech recognition systems , task - oriented dialogue systems provide the foundation of intelligent assistants such as Amazon Alexa , Apple Siri , and Google Assistant . In turn , these assistants allow for natural , personalized interactions with users by tailoring natural language system responses to the dialogue context . We present a theory for the growth dynamics of the World Wide Web that takes into account the wide range of stochastic growth rates in the number of pages per site , as well as the fact that new sites are created at different times . This leads to the prediction of a universal power law in the distribution of the number of pages per site which we confirm experimentally by analyzing data from large crawls made by the search engines Alexa and Infoseek . The existence of this power law not only implies the lack of any length scale for the Web , but also allows one to determine the expected number of sites of any given size without having to exhaustively crawl the Web . Popular conversational agents frameworks such as Alexa Skills Kit ( ASK ) and Google Actions ( gActions ) offer unprecedented opportunities for facilitating the development and deployment of voice-enabled AI solutions in various verticals . Nevertheless , understanding user utterances with high accuracy remains a challenging task with these frameworks . Alexa tool bar will report Alexa company ’s host about the IP and the internet traffic data of user ’s computer . Therefore , website ’s ranking could be figured out via the rates of computers with the Alexa tool bar and Internet traffic data collected . Website ’s ranking roughly tells the website influence degree , but fails to accurately quantify the influence . Alexa tool bar estimated traffic data of some websites . Certified metrics are available with Alexa Pro plans , which gives traffic data accurately by the code installed in the server of the website . Given a website ’s IP address , Alexa ’s Competitive Intelligence toolkit can show the website ’s traffic data including daily unique visitors(UV ) and daily page views per visit(PV ) in its service pages . Purpose – The aim of this paper is to examine the phenomenon of search engine optimization ( SEO ) as a mechanism for improving libraries ' digital content findability on the web . Design/methodology/approach – The study applies web analytical tools , such as Alexa.com , in the collection of data about Canadian libraries ' visibility performance in the ranking of search engine results . Concepts from the Integrated IS&R Research Framework are applied to analyze SEO as an element within the Framework . The conversational nature of intelligent personal assistants ( IPAs ) has the potential to trigger personification tendencies in users , which in turn can translate into consumer loyalty and satisfaction . We conducted a study of Amazon Alexa usage and explored the manifestations and possible correlates of users ' personification of Alexa . The data were collected via diary instrument from nineteen Alexa users over four days . We define filters on streams , both event and sensor streams . For a C-UI we define a taskoid for the creation of state machines for Alexa Controls using the Alexa Gadget API and CLI tools . Why : RAVATTT is a framework for multi sensor fusion and event programming for automation using RPA and state machines . In fact , figuring out all kinds of mechanical and electronic devices and understanding how they work has been a lifelong passion for me . Recently I came across this new revolutionary set of voice controlled Alexa Devices and love the freedom it gives me . I have done a lot of research on Amazon Echo , Amazon Echo Dot and Amazon Tap and this prompted me to put down my learning in the form of a series of books . We examined user interactions with this technology , and focused on the types of tasks requested of Alexa , the variables that affect user behaviors with Alexa , and Alexa ’s alternatives . The data about Alexa usage were collected from 19 participants via the online questionnaire and diary methods over the course of several days . The results indicate that across all age groups , Alexa was primarily used for checking weather forecasts , playing music , and controlling other devices . The use of Amazon 's virtual assistant Alexa in controlling smart home devices is on the rise . The convenience provided by an Alexaenabled device comes at the cost of Alexa service 's voice recording and storage behavior , raising privacy concerns . Amazon claims to record and store voice data in the cloud only when the wake word is spoken . Validation sets consist in 100 queries per intent . Five different cloud - based providers are compared to Snips NLU ( Microsoft ’s Luis , API.AI now Google ’s Dialogflow , Facebook ’s Wit.ai , and Amazon Alexa ) . For more details about the specific methodology for each provider and access to the full dataset , see . We have researched effect of the hyper parameters to model accuracy and we used best hyper parameters for each methods and we aimed to gain best performance for our dataset . This resarch helps applications like virtual assistant with classification of the sentence and giving the output of the class . The output of classification could be a text , image or document . 142301620 . 2018 . The use virtual assistant application in teaching pronunciation ( An Experimental research at second grade of SMAN Krakatau Steel Cilegon ) This research is intended to obtain the empirical evidence about the effect of virtual assistant application in teaching pronunciation at the second grade of SMAN 2 Krakatau steel , the method of this research was a quasi-experimental research which classified as a quantitative research . Moreover , most of those devices heavily rely on cloud-based services , thus transmitting potentially sensitive data to remote servers . To overcome such issues , in this paper we combine some of the most advanced techniques in computer vision , deep learning , speech generation and recognition , and artificial intelligence , into a virtual assistant architecture for smart home automation systems . The proposed assistant is effective and resource-efficient , interactive and customizable , and the realized prototype runs on a low-cost , small-sized , Raspberry PI 3 device . The virtual assistant concept is one that many technology companies have taken on despite having other well-developed and popular user interfaces . We wondered whether it would be possible to create an effective virtual assistant for a medicinal chemistry organization , the key being delivering the information the user would want to see , directly to them , at the right time . The Virtual Assistant Designer . The present paper describes the conceptual and technical design of a new multimodal device named Haptic Desktop System ( HDS ) , which can assist the user in designing/sketching tasks and act as a virtual guide through its force feedback capabilities . CWEs have seen the adoption of application software to addresses business problems as team communication and workload management . Instant messaging solutions , mobile devices and the virtual assistant paradigm have also come into the picture . Software tools in this context lack nonetheless real collaborative features . The objective of this poster is to present ongoing research about the use of virtual assistants in E-government applications . We provide a short state of the art on virtual assistant 's technology . Two case studies are presented and discussed : the web site of the Mexican state of Guanajuato and the Federal Government Citizens Web Page . The existing screen reader software are not suitable for accessing World Wide Web because of the minimum support they provide for web content and the lack of voice recognition . The Virtual Assistant software available in the market are not specifically catered for visually disabled . All the mainstream solutions were analyzed and compared with project Nethra in order to substantiate that the proposed solution is the most optimal and would bridge the ` digital divide ' that exists between sighted and visually disabled users . The classifier was combined with a unique educational system to build the Virtual Operative Assistant which provides users with automated feedback on their metric performance with regards to expert proficiency performance benchmarks . The Virtual Operative Assistant successfully classified skilled and novice participants using 4 metrics with an accuracy , specificity and sensitivity of 92 , 82 and 100 % , respectively . A 2-step feedback system was developed to provide participants with an immediate visual representation of their standing related to expert proficiency performance benchmarks . Following an upsurge in mobile device usage and improvements in speech recognition performance , multiple virtual personal assistant systems have emerged , and have been widely adopted by users . While these assistants proved to be beneficial , their usage has been limited to certain scenarios and domains , with underlying language understanding models that have been finely tuned by their builders . The usage of AI system has increased tremendously over the past few decades . As a result , many AI assistants are available in the market such as Software and Hardware based ( Google Assistant , Amazon Alexa , and Apple Siri ) and Augmented Reality based ( Microsoft HoloLens ) . However , all the current AI system lacks interactive and scope to visualize the output is limited because of certain constraints . This paper describes an AI-based legal assistant that would support case assessment based on the extraction of arguments from court decisions . Open norms are often used in law as a way to set a legislative frame that allows for individual justice under the specific circumstances .
Studies were screened by independent reviewers and Cohen ’s kappa measured inter-coder agreement . Results The database search retrieved 1513 citations ; 17 articles ( 14 different conversational agents ) met the inclusion criteria . Dialogue management strategies were mostly finite-state and frame-based ( 6 and 7 conversational agents , respectively ) ; agent-based strategies were present in one type of system .
To obtain student candidate satisfaction apart from the quality of education must also be accompanied by providing consultation services and information to them . This paper proposes the development of Chatbot which acts as a conversation agent that can play a role of as student candidate service . This Chatbot is called Dinus Intelligent Assistance ( DINA ) .
In this paper we describe a conversational virtual agent that is designed to be used in conjunction with group medical visits to help treat individuals with chronic pain and depression using non-medical treatments including yoga , meditation , and self-massage . Results from two rounds of pilot testing indicate that patients like the virtual agent and find that it helps them manage their condition .
People fundamentally questioned the need for bond and common ground in agent communication , shifting to more utilitarian definitions of conversational qualities . Drawing on these findings we discuss key challenges for conversational agent design , most notably the need to redefine the design parameters for conversational agent interaction .
Third , the Expression of Empathy by which EMMA ’s multiple modalities are triggered through the modulated empathic emotion . The proposed model of empathy is illustrated in a conversational agent scenario involving the virtual humans MAX and EMMA .
The human and machine users of the system have the ability to add , remove , or edit existing information using the CNL , including extensions to the model ( or schema ) in real-time . In this paper we describe various examples undertaken using this approach along with initial experiments using a conversational software agent to enable the field user to interact with such information in full natural English language .
Loneliness and social isolation are significant problems in older adult populations . We describe a conversational agent-based system designed to provide longitudinal social support to isolated older adults . Results from an exploratory pilot study indicate that when the agent proactively draws elders into interactions , it is more effective at addressing loneliness than when the agent passively relies upon elders to initiate interactions .
Cultural differences in humans bargaining behavior are the focus of this study . We investigate the dynamics of human game playing with a conversational computational agent ( Virtual Human ) . We demonstrate that the cultural background influences their observed behavior in this task .
Upon entering the Lobby , they are matched with other students that are logged in to it . Once matched , they are provided with a link to a chat room where they can work with their partner students on a synchronous collaboration activity , supported by a conversational computer agent . Results of a survival model in which we control for level of effort suggest that having experienced a collaborative chat is associated with a slow down in the rate of attrition over time by a factor of two .
marino2016more explicitly incorporate knowledge graphs into an image classification model . Xu2016 created a recall mechanism into a standard LSTM cell that retrieves pieces of external knowledge encoded by a single representation for a conversation model . Concurrently , Dhingra2017 exploit linguistic knowledge using MAGE - GRUs , an adapation of GRUs to handle graphs , however , external knowledge has to be present in form of triples .
Insights from a Comparative Analysis . A chatbot is a software that is able to autonomously communicate with a human being through text and due to its usefulness , an increasing number of businesses are implementing such tools in order to provide timely communication to their clients . In the past , whilst literature has focused on implementing innovative chatbots and the evaluation of such tools , limited studies have been done to critically comparing such conversational systems .
Multiple frameworks have been developed to ease their definition and deployment . While these frameworks are efficient to design simple chatbot applications , they still require advanced technical knowledge to define complex interactions and are difficult to evolve along with the company needs ( e.g. it is typically impossible to change the NL engine provider ) . In addition , the deployment of a chatbot application usually requires a deep understanding of the targeted platforms , especially back-end connections , increasing the development and maintenance costs .
The ensemble model used in this project resulted in a accuracy of 67 % with MFCC features which is the highest when compared to other models . After successful identification of emotions , a chatbot framework is presented which can adapt to interactive dialogues with the customer based on the emotion from the speech in the audio . In addition to this , the results of the previous related work and research gaps are discussed .
But with the recent AI developments , like neural networks and natural language processing , companies like Google , Amazon , or IBM , offers coding-free platforms that can enable a non-technical person to create a chatbot that can fit into their own needs . Using these chatbot platforms , The University of Hong Kong ( HKU ) , through Technology-Enriched Learning Initiative , leverages on its experiences in integrating this technology to better enhance the learning experience of the students . In this workshop , we would like to share our experience gained from developing a set of chatbots for an online blended learning environment .
Nevertheless chatbots are widespread in several applications , especially to provide information to users in a new and enjoyable way . In this chapter we describe different chatbot architectures , exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots : the knowledge base building and the rigidness of the dialogue mechanism .
We will do so in a progressive manner and will make the chatbot in two layers . The first section of the chapter introduces the chatbot concept , followed by a section on implementing a basic rule-based chatbot system . The last section discusses the training of a sequence-to-sequence ( seq2seq ) recurrent neural network ( RNN ) model on a publicly available dataset .
Based on the literature review of intelligent tutoring systems for English instruction and the demand analysis for English instruction in China , and under the guideline of learning theories , such as behaviorism , constructivism and situated learning theory , we have been kept on designing and developing CSIEC intelligent English tutoring system to facilitate the teaching and learning of English in China . Besides the original chatbot function for dialogue simulation , we have developed intelligent vocabulary assessment function and course management function .
Last but not least , we deploy our transfer learning model for PI into our online chatbot system , which can bring in significant improvements over our existing system . Finally , we launch our new system on the chatbot platform Eva in our E-commerce site AliExpress .
Recurrent Neural Network based Sequence-to-sequence ( Seq2Seq ) model is one of the most commonly researched model to implement artificial intelli-gence chatbot and has shown great progress since its introduction in 2014 . However , it is still in infancy and has not been applied widely in educational chatbot development . Introduced originally for neural machine translation , the Seq2Seq model has been adapted for conversation modelling including question-answering chatbots .
Chatbot market can be divided into five regions : North America , Europe , Asia Pacific , Latin America and MEA . Raiffeisen bank implemented the first enterprise chatbot solution in Serbia . REA ( Raiffeisen Electronic Assistant ) is a chatbot built on Weaver platform .
We also discussed the various data sources that are available in designing an enterprise chatbot . There are many chatbot builder platforms and frameworks available in the market that can be used to build chatbots . These frameworks abstract much complex functionality and provide components that are reusable , extendable , and scalable .
The typology dimensions address key characteristics that differentiate current chatbots : the duration of the user ’s relation with the chatbot ( short-term and long-term ) , and the locus of control for user ’s interaction with the chatbot ( user-driven and chatbot-driven ) . To explore the usefulness of the typology , we present four example chatbot purposes for which the typology may support analysis of high-level chatbot interaction design . Furthermore , we analyse a sample of 57 chatbots according to the typology dimensions .
A chatbot is a computer program which can interact with humans through natural language . In this paper , we introduced Jiao Xiao Tong , an interactive question answering chatbot designed in assisting students and faculties in Shanghai Jiao Tong University to accomplish various campus activities such as setting remainders , answering school trivia questions , route navigation and etc . A two-part experiment was conducted to evaluate two aspects of chatbot user experience .
We present a number of solutions and describe the different components of the BOTTA chatbot . The BOTTA database files are publicly available for researchers working on Arabic chatbot technologies . The BOTTA chatbot is also publicly available for any users who want to chat with it online .
The results were derived on base of an online survey among the solution providers . It turned out that a high percentage of the functionalities , which are decisive for a valuable entrepreneurial chatbot application , are covered by the providers , however , with nuanced differences being observed regarding particular features .
The intelligent chat-bot tool will be available 24 hours a day at schools or public libraries or any other location which has internet access . The intelligent chatbot tool will make use of Natural Language Processing techniques to answer the queries by high school students . The intelligent chat-bot tool will be trained on a knowledge base comprising of general knowledge questions and answers .
The renewal of this research is to add access to subject matter features and discussion forum features . These features do not yet exist in the chatbot application system in other studies . Authentication on the chatbot is needed to find out who the user is accessing the chatbot for the material , discussion forum , and work on the problem training and National Examination exercises .
Compared with naive rule-based approaches , our chatbot trained via the PA4C model avoids hand-crafted action selection and is more robust to user utterance variance . The PA4C model optimizes conventional RL models with action parameterization and auxiliary tasks for chatbot training , which address the problems of a large action space and zero-reward states . We evaluate the PA4C model over training a chatbot for calendar event creation tasks .
Focused on the three subprocesses in the chatbot architecture : text processing , semantic understanding , and response generation . Moreover , the survey is conducted with classification of chatbot evaluation methods and their analysis according to chatbot types and three main evaluation schemes ; content evaluation , user satisfaction , and chat function .
This paper introduces a potential solution to provide them with what they are seeking for- a chatbot . The proposed chatbot is a cancer chatbot designed only for people dealing with cancer . People can ask about anything and everything about cancer- symptoms , treatments , survival and so on .
For instance , in the application of machine translation , a task specific sequence score / loss , bilingual evaluation understudy ( BLEU ) , can be adopted to guide the sequence generation . However , in many other practical applications , such as poem generation and chatbot , a task specific loss may not be directly available to score a generated sequence accurately . General adversarial net ( GAN ) proposed by is a promising framework for alleviating the above problem .
subsection : Interaction Layer Interaction mechanism is widely used in tasks of matching source and target textual contents , such as natural language inference and retrieve - based chatbot . The key idea of interaction mechanism is to use the interaction features between the small units ( e.g. , words in the textual contents ) to infer fine - grained clues whether two contents are matching .
The study includes the task analysis of some of the user 's specific needs in everyday life , the problems faced by the user while trying to do them , a brief description of the workarounds and their degree of usability in terms of efficiency and satisfaction . While the combination of VoiceOver and Siri gives the user some degree of accessibility , the most notorious access problems were the difficulty to do manual gestures involving more than one finger , and editing text with the keyboard . Besides the obvious need to continue analyzing voice and manual interaction modes , it is required the exploration of other gesture controls on the device , or the use of alternative gadgets in order to improve the mobile accessibility of people with multiple disabilities .
Bots , Virtual Assistants and Virtual Agents are well known in a personal environment . Technologies like “ Apple Siri ” or “ Amazon Alexa ” serve as digital assistants to enhance both accessibility and productivity . Yet , these technologies have to play with different rules in the enterprise context .
This paper formulates two stochastic nonautonomous SIRI epidemic systems with nonlinear perturbations . The main aim of this study is to investigate stochastic dynamics of the two SIRI epidemic systems and obtain their thresholds . For the nonautonomous stochastic SIRI epidemic system with white noise , the authors provide analytic results regarding the stochastic boundedness , stochastic permanence and persistence in mean . Moreover , the authors prove that the system has at least one nontrivial positive T-periodic solution by using Lyapunov function and Hasminskii ’s theory .
The method used in this research proposed three tasks and usability was investigated from the performance analysis based on time and perceptions of the volunteers through questionnaires . Age was found not to be the only factor influencing the usability of the Siri virtual assistant . Other factors , such as prior knowledge , education level and personal motivation , are capable of influencing the research results of usability criteria .
The results also demonstrate that information service providers should always offer mobile-friendly interfaces ( i.e. , RESTful web services with JSON encoding ) when possible . The benchmarking software is made available as an open-source application so that others can perform their own experiments , and so that app developers can use this library as a foundation for building new applications based on the SIRI format .
Steve Muskal of Eidogen-Sertanty [ 3 ] remarks on the power of voice recognition : Siri can achieve greater than 90 % accuracy even with science terms . Amazon has a Siri-like device [ 4 ] which does far field listening . Muskal adds that he can capture and analyze audio with a recording app ( RecordUp ) that detects breaks , and uploads segments to Dropbox .
The purpose of this study was to investigate the importance of intelligent personal assistants ' speech for the user experience and if it increases with more naturalness . The intelligent personal assistant Siri was chosen to perform an experiment with repeated measures design consisting of three levels : Siri 's speech , natural speech mimicking Siri 's prosody and natural speech . The results revealed no statistically significant difference between the three levels .
INVESTIGATING SIRI AS A VIRTUAL ASSISTANT IN A LEARNING CONTEXT ? . In this paper , we address challenges arising from the use of the conversational interface Siri during a literacy activity in a learning context . On one hand , we investigate potentialities of Siri as a virtual assistant and knowledge navigator for task accomplishment .
Task oriented dialogue systems can reduce operating costs by automating processes such as call center dispatch and online customer support . Moreover , when combined with automatic speech recognition systems , task - oriented dialogue systems provide the foundation of intelligent assistants such as Amazon Alexa , Apple Siri , and Google Assistant . In turn , these assistants allow for natural , personalized interactions with users by tailoring natural language system responses to the dialogue context .
We present a theory for the growth dynamics of the World Wide Web that takes into account the wide range of stochastic growth rates in the number of pages per site , as well as the fact that new sites are created at different times . This leads to the prediction of a universal power law in the distribution of the number of pages per site which we confirm experimentally by analyzing data from large crawls made by the search engines Alexa and Infoseek . The existence of this power law not only implies the lack of any length scale for the Web , but also allows one to determine the expected number of sites of any given size without having to exhaustively crawl the Web .
Popular conversational agents frameworks such as Alexa Skills Kit ( ASK ) and Google Actions ( gActions ) offer unprecedented opportunities for facilitating the development and deployment of voice-enabled AI solutions in various verticals . Nevertheless , understanding user utterances with high accuracy remains a challenging task with these frameworks .
Alexa tool bar will report Alexa company ’s host about the IP and the internet traffic data of user ’s computer . Therefore , website ’s ranking could be figured out via the rates of computers with the Alexa tool bar and Internet traffic data collected . Website ’s ranking roughly tells the website influence degree , but fails to accurately quantify the influence .
Alexa tool bar estimated traffic data of some websites . Certified metrics are available with Alexa Pro plans , which gives traffic data accurately by the code installed in the server of the website . Given a website ’s IP address , Alexa ’s Competitive Intelligence toolkit can show the website ’s traffic data including daily unique visitors(UV ) and daily page views per visit(PV ) in its service pages .
Purpose – The aim of this paper is to examine the phenomenon of search engine optimization ( SEO ) as a mechanism for improving libraries ' digital content findability on the web . Design/methodology/approach – The study applies web analytical tools , such as Alexa.com , in the collection of data about Canadian libraries ' visibility performance in the ranking of search engine results . Concepts from the Integrated IS&R Research Framework are applied to analyze SEO as an element within the Framework .
The conversational nature of intelligent personal assistants ( IPAs ) has the potential to trigger personification tendencies in users , which in turn can translate into consumer loyalty and satisfaction . We conducted a study of Amazon Alexa usage and explored the manifestations and possible correlates of users ' personification of Alexa . The data were collected via diary instrument from nineteen Alexa users over four days .
We define filters on streams , both event and sensor streams . For a C-UI we define a taskoid for the creation of state machines for Alexa Controls using the Alexa Gadget API and CLI tools . Why : RAVATTT is a framework for multi sensor fusion and event programming for automation using RPA and state machines .
In fact , figuring out all kinds of mechanical and electronic devices and understanding how they work has been a lifelong passion for me . Recently I came across this new revolutionary set of voice controlled Alexa Devices and love the freedom it gives me . I have done a lot of research on Amazon Echo , Amazon Echo Dot and Amazon Tap and this prompted me to put down my learning in the form of a series of books .
We examined user interactions with this technology , and focused on the types of tasks requested of Alexa , the variables that affect user behaviors with Alexa , and Alexa ’s alternatives . The data about Alexa usage were collected from 19 participants via the online questionnaire and diary methods over the course of several days . The results indicate that across all age groups , Alexa was primarily used for checking weather forecasts , playing music , and controlling other devices .
The use of Amazon 's virtual assistant Alexa in controlling smart home devices is on the rise . The convenience provided by an Alexaenabled device comes at the cost of Alexa service 's voice recording and storage behavior , raising privacy concerns . Amazon claims to record and store voice data in the cloud only when the wake word is spoken .
Validation sets consist in 100 queries per intent . Five different cloud - based providers are compared to Snips NLU ( Microsoft ’s Luis , API.AI now Google ’s Dialogflow , Facebook ’s Wit.ai , and Amazon Alexa ) . For more details about the specific methodology for each provider and access to the full dataset , see .
We have researched effect of the hyper parameters to model accuracy and we used best hyper parameters for each methods and we aimed to gain best performance for our dataset . This resarch helps applications like virtual assistant with classification of the sentence and giving the output of the class . The output of classification could be a text , image or document .
142301620 . 2018 . The use virtual assistant application in teaching pronunciation ( An Experimental research at second grade of SMAN Krakatau Steel Cilegon ) This research is intended to obtain the empirical evidence about the effect of virtual assistant application in teaching pronunciation at the second grade of SMAN 2 Krakatau steel , the method of this research was a quasi-experimental research which classified as a quantitative research .
Moreover , most of those devices heavily rely on cloud-based services , thus transmitting potentially sensitive data to remote servers . To overcome such issues , in this paper we combine some of the most advanced techniques in computer vision , deep learning , speech generation and recognition , and artificial intelligence , into a virtual assistant architecture for smart home automation systems . The proposed assistant is effective and resource-efficient , interactive and customizable , and the realized prototype runs on a low-cost , small-sized , Raspberry PI 3 device .
The virtual assistant concept is one that many technology companies have taken on despite having other well-developed and popular user interfaces . We wondered whether it would be possible to create an effective virtual assistant for a medicinal chemistry organization , the key being delivering the information the user would want to see , directly to them , at the right time .
The Virtual Assistant Designer . The present paper describes the conceptual and technical design of a new multimodal device named Haptic Desktop System ( HDS ) , which can assist the user in designing/sketching tasks and act as a virtual guide through its force feedback capabilities .
CWEs have seen the adoption of application software to addresses business problems as team communication and workload management . Instant messaging solutions , mobile devices and the virtual assistant paradigm have also come into the picture . Software tools in this context lack nonetheless real collaborative features .
The objective of this poster is to present ongoing research about the use of virtual assistants in E-government applications . We provide a short state of the art on virtual assistant 's technology . Two case studies are presented and discussed : the web site of the Mexican state of Guanajuato and the Federal Government Citizens Web Page .
The existing screen reader software are not suitable for accessing World Wide Web because of the minimum support they provide for web content and the lack of voice recognition . The Virtual Assistant software available in the market are not specifically catered for visually disabled . All the mainstream solutions were analyzed and compared with project Nethra in order to substantiate that the proposed solution is the most optimal and would bridge the ` digital divide ' that exists between sighted and visually disabled users .
The classifier was combined with a unique educational system to build the Virtual Operative Assistant which provides users with automated feedback on their metric performance with regards to expert proficiency performance benchmarks . The Virtual Operative Assistant successfully classified skilled and novice participants using 4 metrics with an accuracy , specificity and sensitivity of 92 , 82 and 100 % , respectively . A 2-step feedback system was developed to provide participants with an immediate visual representation of their standing related to expert proficiency performance benchmarks .
Following an upsurge in mobile device usage and improvements in speech recognition performance , multiple virtual personal assistant systems have emerged , and have been widely adopted by users . While these assistants proved to be beneficial , their usage has been limited to certain scenarios and domains , with underlying language understanding models that have been finely tuned by their builders .
The usage of AI system has increased tremendously over the past few decades . As a result , many AI assistants are available in the market such as Software and Hardware based ( Google Assistant , Amazon Alexa , and Apple Siri ) and Augmented Reality based ( Microsoft HoloLens ) . However , all the current AI system lacks interactive and scope to visualize the output is limited because of certain constraints .
This paper describes an AI-based legal assistant that would support case assessment based on the extraction of arguments from court decisions . Open norms are often used in law as a way to set a legislative frame that allows for individual justice under the specific circumstances .
Conversational agents in healthcare: a systematic review Dinus Intelligent Assistance (DINA) Chatbot for University Admission Services Blissful Agents: Adjuncts to Group Medical Visits for Chronic Pain and Depression What Makes a Good Conversation?: Challenges in Designing Truly Conversational Agents Empathy-Based Emotional Alignment for a Virtual Human: A Three-Step Approach Building a “living database” for human-machine intelligence analysis Addressing Loneliness and Isolation in Older Adults: Proactive Affective Agents Provide Better Support Cultural Differences in Playing Repeated Ultimatum Game Online with Virtual Humans Positive Impact of Collaborative Chat Participation in an edX MOOC Dynamic Integration of Background Knowledge in Neural NLU Systems AIML and Sequence-to-Sequence Models to Build Artificial Intelligence Chatbots: Insights from a Comparative Analysis Xatkit: A Multimodal Low-Code Chatbot Development Framework Detection of Audio Emotional Intelligence Using Machine Learning Algorithms Zero-coding Chatbot for blended learning: Basics in kick-starting your own bot! Chatbots as Interface to Ontologies Developing a Chatbot From Chatbot to Vocabulary Assessment and Course Management Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce Sequence to Sequence Model Performance for Education Chatbot Entry Market Strategy for Weaver Chatbot using the Digital B2B Model A Novel In-House Implementation of a Chatbot Framework Different Chatbots for Different Purposes: Towards a Typology of Chatbots to Understand Interaction Design A Study of User Experience in Knowledge-Based QA Chatbot Design Botta: An Arabic Dialect Chatbot Comparison of Commercial Chatbot solutions for Supporting Customer Interaction Developing an Intelligent Chat-bot Tool to Assist High School Students for Learning General Knowledge Subjects Learning Support System using Chatbot in "Kejar C Package" Homeschooling Program Context-Uncertainty-Aware Chatbot Action Selection via Parameterized Auxiliary Reinforcement Learning A Survey on Evaluation Methods for Chatbots A Graph Based Chatbot for Cancer Patients SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient Explicit Interaction Model towards Text Classification Mobile Accessibility for People with Combined Visual and Motor Impairment: A case Study Defining Bots in an Enterprise Context Periodic Solution and Ergodic Stationary Distribution of Stochastic SIRI Epidemic Systems with Nonlinear Perturbations Evaluating the Usability of the Siri Virtual Assistant on Mobile Devices with Emphasis on Brazilian Elderly Users Performance Evaluation of Transit Data Formats on a Mobile Device App-etite for change Bör intelligenta assistenter tala naturligt? En undersökning om betydelsen av intelligenta assistenters tal för användarupplevelsen HEY SIRI, WHAT CAN I TELL ABOUT SANCHO PANZA IN MY PRESENTATION? INVESTIGATING SIRI AS A VIRTUAL ASSISTANT IN A LEARNING CONTEXT? Global-Locally Self-Attentive Dialogue State Tracker Evolutionary Dynamics of the World Wide Web Building chatbots from large scale domain-specific knowledge bases: challenges and opportunities Web Communication Impact Model and Its Application in the Analysis of Media’s Web Sites Increasing Libraries' Content Findability on the Web with Search Engine Optimization Personification of the Amazon Alexa: BFF or a Mindless Companion Two Motor Designs with a Reactive Design to Lego Mindstorm Ev3, Based Sensor-Actions Framework Using Ravattt. Amazon Echo Dot: Amazon Dot Advanced User Guide (2017 Updated) Step-by-Step Instructions to Enrich Your Smart Life! (Amazon Echo, Dot, Echo Dot, Amazon Echo User Manual, Echo Dot ebook, Amazon Dot) Talk to me: Exploring user interactions with the Amazon Alexa Alexa's Voice Recording Behavior: A Survey of User Understanding and Awareness Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces Sentence Classification with Deep Learning Method For Virtual Assistant Applications The use virtual assistant application in teaching pronunciation ( An Experimental research at second grade of SMAN Krakatau Steel Cilegon) A Vision and Speech Enabled, Customizable, Virtual Assistant for Smart Environments Creating a Virtual Assistant for Medicinal Chemistry. Haptic Desktop: The Virtual Assistant Designer *Thing: Improve Anything to Anything Collaboration Virtual assistants for e-government: a preliminary study Project Nethra - an intelligent assistant for the visually disabled to interact with internet services The Virtual Operative Assistant: An explainable artificial intelligence tool for simulation-based training in surgery and medicine Keynote: Graph-based Approaches for Spoken Language Understanding 3D Holographic and Interactive Artificial Intelligence System Distilling Jurisprudence through Argument Mining for Case Assessment
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