Abstract: A computer implemented method for automatic speech analysis comprising setting a target phrase, the target phrase comprising a target phoneme, the target phoneme having corresponding target values of a set of phonological features associated therewith, wherein each target value is one of: an indication that the phonological feature should be present, an indication that the phonological feature should be absent, or an indication that the presence of the phonological feature is not specified, receiving a speech signal, wherein the speech signal comprises a user's attempt to say the target phrase, analysing the speech signal to determine the phonological features present within a portion of the speech signal corresponding to the target phoneme and assigning a probability to each of the set of phonological features, comparing the probability assigned to each phonological feature based on the speech signal to the expected target value of that phonological feature within the phrase, determining a deviation from the

Abstract: A computer implemented method for automatic speech analysis comprising setting a target phrase, the target phrase comprising a target phoneme, the target phoneme having corresponding target values of a set of phonological features associated therewith, wherein each target value is one of: an indication that the phonological feature should be present, an indication that the phonological feature should be absent, or an indication that the presence of the phonological feature is not specified, receiving a speech signal, wherein the speech signal comprises a user's attempt to say the target phrase, analysing the speech signal to determine the phonological features present within a portion of the speech signal corresponding to the target phoneme and assigning a probability to each of the set of phonological features, comparing the probability assigned to each phonological feature based on the speech signal to the expected target value of that phonological feature within the phrase, determining a deviation from the

Abstract: The invention provides a method of automatic speech recognition. The method includes receiving a speech signal, dividing the speech signal into time windows, for each time window determining acoustic parameters of the speech signal within that window, and identifying phonological features from the acoustic parameters, such that a sequence of phonological features are generated for the speech signal, separating the sequence of phonological features into a sequence of zones, and comparing the sequences of zones to a lexical entry comprising a sequence of phonological segments to a stored lexicon to identify one or more words in the speech signal.

Abstract: The invention provides a method of automatic speech recognition. The method includes receiving a speech signal, dividing the speech signal into time windows, for each time window determining acoustic parameters of the speech signal within that window, and identifying phonological features from the acoustic parameters, such that a sequence of phonological features are generated for the speech signal, separating the sequence of phonological features into a sequence of zones, and comparing the sequences of zones to a lexical entry comprising a sequence of phonological segments to a stored lexicon to identify one or more words in the speech signal.

Abstract: A method of automatic speech recognition, the method comprising the steps of receiving a speech signal, dividing the speech signal into time windows, for each time window, determining acoustic parameters of the speech signal within that window, and identifying speech features from the acoustic parameters, such that a sequence of speech features are generated for the speech signal, separating the sequence of speech features into a sequence of phonological segments, and comparing the sequential phonological segments to a stored lexicon to identify one or more words in the speech signal.

Abstract: A method of automatic speech recognition, the method comprising the steps of receiving a speech signal, dividing the speech signal into time windows, for each time window, determining acoustic parameters of the speech signal within that window, and identifying speech features from the acoustic parameters, such that a sequence of speech features are generated for the speech signal, separating the sequence of speech features into a sequence of phonological segments, and comparing the sequential phonological segments to a stored lexicon to identify one or more words in the speech signal.