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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def detect_interval( self, min_head_length=None, max_head_length=None, min_tail_length=None, max_tail_length=None ):
 """ Detect the interval of the audio file containing the fragments in the text file. Return the audio interval as a tuple of two :class:`~aeneas.exacttiming.TimeValue` objects, representing the begin and end time, in seconds, with respect to the full wave duration. If one of the parameters is ``None``, the default value (``0.0`` for min, ``10.0`` for max) will be used. :param min_head_length: estimated minimum head length :type min_head_length: :class:`~aeneas.exacttiming.TimeValue` :param max_head_length: estimated maximum head length :type max_head_length: :class:`~aeneas.exacttiming.TimeValue` :param min_tail_length: estimated minimum tail length :type min_tail_length: :class:`~aeneas.exacttiming.TimeValue` :param max_tail_length: estimated maximum tail length :type max_tail_length: :class:`~aeneas.exacttiming.TimeValue` :rtype: (:class:`~aeneas.exacttiming.TimeValue`, :class:`~aeneas.exacttiming.TimeValue`) :raises: TypeError: if one of the parameters is not ``None`` or a number :raises: ValueError: if one of the parameters is negative """

        head = self.detect_head(min_head_length, max_head_length)
        tail = self.detect_tail(min_tail_length, max_tail_length)
        begin = head
        end = self.real_wave_mfcc.audio_length - tail
        self.log([u"Audio length: %.3f", self.real_wave_mfcc.audio_length])
        self.log([u"Head length:  %.3f", head])
        self.log([u"Tail length:  %.3f", tail])
        self.log([u"Begin:        %.3f", begin])
        self.log([u"End:          %.3f", end])
        if (begin >= TimeValue("0.000")) and (end > begin):
            self.log([u"Returning %.3f %.3f", begin, end])
            return (begin, end)
        self.log(u"Returning (0.000, 0.000)")
        return (TimeValue("0.000"), TimeValue("0.000"))