Method for automatically punctuating a speech utterance in a continuous speech recognition system
First Claim
1. In a speech recognition system that outputs a sequence of decoded words, a method for automatically punctuating the sequence of decoded words comprises the steps of:
- in a vocabulary that defines items in a language model, the items including words and punctuation marks, assigning at least one baseform to each of the punctuation marks, the at least one baseform corresponding to at least one of silence and a non-word noise;
in the language model, defining conditional probabilities for each of the punctuation marks based upon at least one of at least one preceding word and at least one succeeding word; and
automatically inserting a subject punctuation mark at a given point in the sequence of decoded words when an acoustic score and a language model score associated with the subject punctuation mark produce a higher combined likelihood than the acoustic score and the language model score associated with any other item in the vocabulary for the given point in the sequence of decoded words.
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Abstract
In a speech recognition system which recognizes a spoken utterance consisting of a sequence of spoken words and, in response, outputs a sequence of decoded words, a method for automatically punctuating the sequence of decoded words is provided. In a vocabulary of items including words, silences, and punctuation marks, assigning at least one baseform to each punctuation mark corresponding to one of silence and a non-word noise. Additionally, the method includes the step of automatically inserting a subject punctuation mark at a given point in the sequence of decoded words when an acoustic score and a language model score associated with the subject punctuation mark produce a higher combined likelihood than the acoustic score and the language model score associated with any other item in the vocabulary for the given point in the sequence of decoded words.
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Citations
29 Claims
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1. In a speech recognition system that outputs a sequence of decoded words, a method for automatically punctuating the sequence of decoded words comprises the steps of:
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in a vocabulary that defines items in a language model, the items including words and punctuation marks, assigning at least one baseform to each of the punctuation marks, the at least one baseform corresponding to at least one of silence and a non-word noise; in the language model, defining conditional probabilities for each of the punctuation marks based upon at least one of at least one preceding word and at least one succeeding word; and automatically inserting a subject punctuation mark at a given point in the sequence of decoded words when an acoustic score and a language model score associated with the subject punctuation mark produce a higher combined likelihood than the acoustic score and the language model score associated with any other item in the vocabulary for the given point in the sequence of decoded words. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. In a speech recognition system which recognizes a spoken utterance and, in response, outputs a sequence of decoded words, a method for automatically punctuating the sequence of decoded words comprises the steps of:
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assigning at least one baseform to a subject punctuation mark in a vocabulary of words and punctuation marks, the at least one baseform including at least one of a silence phone, two consecutive silence phones, at least one consonant phone preceded and followed by the silence phone, at least one vowel phone preceded and followed by the silence phone, and at least one consonant phone and at least one vowel phone preceded and followed by the silence phone, the vocabulary defining items for which language model scores exist; defining at least one conditional probability for the subject punctuation mark in a language model based upon at least one of at least one preceding word and at least one succeeding word; and generating a word match score corresponding to the probability that the subject punctuation mark corresponds to acoustic data generated by said utterance; generating a language model score corresponding to the probability that the subject punctuation mark corresponds to the acoustic data generated by said utterance; and automatically inserting the subject punctuation mark at a given position in the sequence of decoded words when the combination of the word match score and the language model score produces the highest combined likelihood over any other word and punctuation mark in the vocabulary for the given position. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18)
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19. In a speech recognition system which recognizes a spoken utterance consisting of an input sequence of spoken words and outputs a sequence of decoded words, a method for automatically punctuating the decoded words comprises the steps of:
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training an acoustic model; training an n-gram language model; building a vocabulary of items, the items including words and punctuation marks, said building step including assigning at least one baseform to each of the punctuation marks in the vocabulary, the at least one baseform corresponding to at least one of silence and a non-word noise, the vocabulary defining the items for which language model scores exist; defining conditional probabilities for the punctuation marks in the language model based upon at least one of at least one preceding word and at least one succeeding word; and generating a word match score corresponding to the probability that a subject punctuation mark in the vocabulary corresponds to acoustic data generated by said utterance; generating a language model score corresponding to the probability that the subject punctuation mark corresponds to acoustic data generated by said utterance; and automatically inserting the subject punctuation mark at a given point in the sequence of decoded words when the combination of the word match score and the language model score produces the highest combined likelihood over any other item in the vocabulary for the given point. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27, 28, 29)
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Specification