Knowledge-based speech recognition system and methods having frame length computed based upon estimated pitch period of vocalic intervals

A knowledge-based speech recognition system for recognizing an input speech signal, the input speech signal including a sequence of phonemes, the system comprising:

• means for capturing the input speech signal;
• means for segmenting the input speech signal into a series of segments including vocalic intervals and non-vocalic intervals, the vocalic intervals having a frame length computed based on an estimation of the pitch period of the vocalic intervals of the input speech signal, the series of segments approximately corresponding to the sequence of phonemes;
• means for characterizing the series of segments based upon acoustic events detected within the input speech signal to obtain an acoustic feature vector;
• means for storing a dictionary having a multiplicity of words, each one of the multiplicity of words described by a phonetic transcription and an acoustic event transcription, the acoustic event transcription comprising a lattice of acoustic events corresponding to a plurality of pronunciations;
• and
• means for selecting a word choice by comparing the acoustic feature vector to selected lattices of acoustic event transcriptions.

A knowledge-based speech recognition system for recognizing an input speech signal, the input speech signal including a sequence of phonemes, the system comprising:

• means for capturing the input speech signal;
• means for segmenting the input speech signal into a series of segments including vocalic intervals and non-vocalic intervals, the vocalic intervals having a frame length computed based on an estimation of the pitch period of the vocalic intervals of the input speech signal, the series of segments approximately corresponding to the sequence of phonemes;
• means for characterizing the acoustic and spectral characteristics of the input speech signal:
• means for storing a dictionary having a multiplicity of words, each one of the multiplicity of words described by a series of acoustic events, spectral characteristics and a series of grammatical, semantic and syntactic attributes;
• and
• means for selecting a word choice from amongst the multiplicity of words by weighing, for one or more of the multiplicity of words, correspondence between the acoustic events and the acoustic characteristics, between the spectral characteristics of the words and the input speech signal, and the grammatical, semantic and syntactic attributes of the words.

A method of applying knowledge-based rules in a processor-based system to recognize an input speech signal as a word in a natural language, the input speech signal comprising vocalic and non-vocalic intervals, each of the vocalic intervals having a pitch period, the method comprising steps of:

• capturing and storing the input speech signal;
• segmenting the input speech signal into a series of segments including vocalic intervals and non-vocalic intervals, the vocalic intervals having a frame length computed based on an estimation of the pitch period of the vocalic intervals of the input speech signal;
• generating an acoustic feature vector by characterizing the series of segments based upon acoustic events detected within the input speech signal;
• retrieving from a store a dictionary having a multiplicity of words, each one of the multiplicity of words described by a phonetic transcription and at least one acoustic event transcription;
• and
• comparing the acoustic feature vector to the acoustic event transcriptions of the multiplicity of words to select a word choice.

A method of applying knowledge-based rules in a processor-based system to recognize an input speech signal as a word in a natural language, the input speech signal including a sequence of phonemes, the method comprising steps of:

• capturing and storing the input speech signal;
• segmenting the input speech signal into a series of segments including vocalic intervals and non-vocalic intervals, the vocalic intervals having a frame length computed based on an estimation of the pitch period of the vocalic intervals of the input speech signal, the series of segments approximately corresponding to the sequence of phonemes;
• generating an acoustic feature vector by characterizing the series of segments based upon acoustic events detected within the input speech signal;
• retrieving from a store a dictionary having a multiplicity of words, each one of the multiplicity of words described by a phonetic transcription and an acoustic event transcription, the acoustic event transcription comprising a lattice of acoustic events corresponding to a plurality of pronunciations;
• and
• comparing the acoustic feature vector to selected lattices of acoustic event transcriptions to select a word choice.

A method of applying knowledge-based rules in a processor-based system to recognize an input speech signal as a word in a natural language, the input speech signal including a sequence of phonemes, the method comprising steps of:

• capturing and storing the input speech signal;
• segmenting the input speech signal into a series of segments including vocalic intervals and non-vocalic intervals, the vocalic intervals having a frame length computed based on an estimation of the pitch period of the vocalic intervals of the input speech signal, the series of segments approximately corresponding to the sequence of phonemes;
• computing acoustic and spectral characteristics representative of the input speech signal;
• retrieving from a store a dictionary having a multiplicity of words, each one of the multiplicity of words described by a series of acoustic events, spectral characteristics and a series of grammatical, semantic and syntactic attributes;
• and
• selecting a word choice from amongst the multiplicity of words by weighing, for one or more of the multiplicity of words, correspondence between the acoustic events and the acoustic characteristics, between the spectral characteristics of the words and the input speech signal, and the grammatical, semantic and syntactic attributes of the words.