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公开(公告)号：CA2073991C
公开(公告)日：1996-08-06
申请号：CA2073991
申请日：1992-07-16
Applicant: IBM
Abstract: A speech coding and speech recognition apparatus. The value of at least one feature of an utterance is measured over each of a series of successive time intervals to produce a series of feature vector signals. The closeness of the feature value of each feature vector signal to the parameter value of each of a set of prototype vector signals is determined to obtain prototype match scores for each vector signal and each prototype vector signal. For each feature vector signal, first-rank and second-rank scores are associated with the prototype vector signals having the best and second best prototype match scores, respectively. For each feature vector signal, at least the identification value and the rank score of the first-ranked and second-ranked prototype vector signals are output as a coded utterance representation signal of the feature vector signal, to produce a series of coded utterance representation signals. For each of a plurality of speech units, a probabilistic model has a plurality of model outputs, and output probabilities for each model output. Each model output comprises the identification value of a prototype vector and a rank score. For each speech unit, a match score comprises an estimate of the probability that the probabilistic model of the speech unit would output a series of model outputs matching a reference series comprising the identification value and rank score of at least one prototype vector from each coded utterance representation signal in the series of coded utterance representation signals.
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公开(公告)号：DE3876379D1
公开(公告)日：1993-01-14
申请号：DE3876379
申请日：1988-09-16
Applicant: IBM
Inventor： PICHENY MICHAEL ALAN , NAHAMOO DAVID , DE SOUZA PETER VINCENT , BROWN PETER FITZHUGH
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公开(公告)号：DE69129015D1
公开(公告)日：1998-04-09
申请号：DE69129015
申请日：1991-12-10
Applicant: IBM
Inventor： NAHAMOO DAVID , DE SOUZA PETER VINCENT , BAHL LALIT R , PICHENY MICHAEL ALAN
Abstract: The present invention is related to speech recognition and particularly to a new type of vector quantizer and a new vector quantization technique in which the error rate of associating a sound with an incoming speech signal is drastically reduced. To achieve this end, the present invention technique groups the feature vectors in a space into different prototypes at least two of which represent a class of sound. Each of the prototypes may in turn have a number of subclasses or partitions. Each of the prototypes and their subclasses may be assigned respective identifying values. To identify an incoming speech feature vector, at least one of the feature values of the incoming feature vector is compared with the different values of the respective prototypes, or the subclasses of the prototypes. The class of sound whose group of prototypes, or at least one of the prototypes, whose combined value most closely matches the value of the feature value of the feature vector is deemed to be the class corresponding to the feature vector. The feature vector is then labeled with the identifier associated with that class.
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公开(公告)号：DE69129015T2
公开(公告)日：1998-10-29
申请号：DE69129015
申请日：1991-12-10
Applicant: IBM
Inventor： NAHAMOO DAVID , DE SOUZA PETER VINCENT , BAHL LALIT R , PICHENY MICHAEL ALAN
Abstract: The present invention is related to speech recognition and particularly to a new type of vector quantizer and a new vector quantization technique in which the error rate of associating a sound with an incoming speech signal is drastically reduced. To achieve this end, the present invention technique groups the feature vectors in a space into different prototypes at least two of which represent a class of sound. Each of the prototypes may in turn have a number of subclasses or partitions. Each of the prototypes and their subclasses may be assigned respective identifying values. To identify an incoming speech feature vector, at least one of the feature values of the incoming feature vector is compared with the different values of the respective prototypes, or the subclasses of the prototypes. The class of sound whose group of prototypes, or at least one of the prototypes, whose combined value most closely matches the value of the feature value of the feature vector is deemed to be the class corresponding to the feature vector. The feature vector is then labeled with the identifier associated with that class.
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公开(公告)号：DE69221403T2
公开(公告)日：1998-02-19
申请号：DE69221403
申请日：1992-05-20
Applicant: IBM
Inventor： BAHL LALIT R , BELLEGARDA JEROME R , DE SOUZA PETER VINCENT , NAHAMOO DAVID , PICHENY MICHAEL ALAN
Abstract: An apparatus for generating a set of acoustic prototype signals for encoding speech includes means for storing a training script model comprises a series of word-segment models. Each word-segment model comprises a series of elementary models. Means are provided for measuring the value of at least one feature of an utterance of the training script during each of a series of time intervals to produce a series of feature vector signals representing the feature values of the utterance. Means are provided for estimating at least one path through the training script model which would produce the entire series of measured feature vector signals. From the estimated path, the elementary model in the training script model which would produce each feature vector signal is estimated. The apparatus further comprises means for clustering the feature vector signals into a plurality of clusters. Each feature vector signal in a cluster corresponds to a single elementary model in a single location in a single word-segment model. Each cluster signal has a cluster value equal to an average of the feature values of all feature vectors in the signal. Finally, the apparatus includes means for storing a plurality of prototype vector signals. Each prototype vector signal corresponds to an elementary model, has an identifier, and comprises at least two partition values. The partition values are equal to combinations of the cluster values of one or more cluster signals corresponding to the elementary model.
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Patent Agency Ranking
公开(公告)号：DE3876379T2
公开(公告)日：1993-06-09
申请号：DE3876379
申请日：1988-09-16
Applicant: IBM
Inventor： PICHENY MICHAEL ALAN , NAHAMOO DAVID , DE SOUZA PETER VINCENT , BROWN PETER FITZHUGH
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公开(公告)号：DE69221403D1
公开(公告)日：1997-09-11
申请号：DE69221403
申请日：1992-05-20
Applicant: IBM
Inventor： BAHL LALIT R , BELLEGARDA JEROME R , DE SOUZA PETER VINCENT , NAHAMOO DAVID , PICHENY MICHAEL ALAN
Abstract: An apparatus for generating a set of acoustic prototype signals for encoding speech includes means for storing a training script model comprises a series of word-segment models. Each word-segment model comprises a series of elementary models. Means are provided for measuring the value of at least one feature of an utterance of the training script during each of a series of time intervals to produce a series of feature vector signals representing the feature values of the utterance. Means are provided for estimating at least one path through the training script model which would produce the entire series of measured feature vector signals. From the estimated path, the elementary model in the training script model which would produce each feature vector signal is estimated. The apparatus further comprises means for clustering the feature vector signals into a plurality of clusters. Each feature vector signal in a cluster corresponds to a single elementary model in a single location in a single word-segment model. Each cluster signal has a cluster value equal to an average of the feature values of all feature vectors in the signal. Finally, the apparatus includes means for storing a plurality of prototype vector signals. Each prototype vector signal corresponds to an elementary model, has an identifier, and comprises at least two partition values. The partition values are equal to combinations of the cluster values of one or more cluster signals corresponding to the elementary model.
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公开(公告)号：DE69028842D1
公开(公告)日：1996-11-14
申请号：DE69028842
申请日：1990-12-13
Applicant: IBM
Inventor： BELLEGARDA JEROME R , DE SOUZA PETER VINCENT , GOPALAKRISHNAN PONANI S , NAHAMOO DAVID , PICHENY MICHAEL ALAN
Abstract: A method and apparatus of modeling a word by concatenating a series of elemental models to form a word model. At least one elemental model in the series is a composite elemental model formed by combining the starting states of at least first and second primitive elemental models. Each primitive elemental model represents a speech component. The primitive elemental models are combined by a weighted combination of their parameters in proportion to the values of the weighting factors. In order to tailor the word model to closely represent variations in the pronunciation of the word, the word is uttered a plurality of times by a plurality of different speakers. From the prior values of the weighting factors, and from the values of the parameters of the first and second primitive elemental models, the conditional probability of occurrence of the first primitive elemental model given the occurrence of the composite elemental model and given the occurrence of the observed sequence of component sounds is estimated. A posterior value for the first weighting factor is estimated from the conditional probability. By constructing word models from composite elemental models, and by constructing composite elemental models from primitive elemental models, it is possible for the resulting word model to closely represent many variations in the pronunciation of a word. By providing a relatively small set of primitive elemental models in comparison to a relatively large vocabulary of words, the models can be trained to the voice of a new speaker by having the new speaker utter only a small subset of the words in the vocabulary.
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