Oki Electric Industry Co., Ltd.

Yukio Tabei

Makoto Morito

Kozo Yamada

Akihiko Fujisawa

Keiko Takahashi

Masao Takeuchi

The principal object of this invention is to provide a suitable control method for closing length with respect to phonemes (such as unvoiced plosive consonants) having a closing interval, and as a result an improved rule-based speech synthesis device is provided. A phoneme type judgement partjudges whether the phoneme in question is a vowel or consonant and, in the case of a consonant, judges whether or not it is a consonant that anteriorly has a closing interval. As a result, it operates a vowel length estimation partwhen it judges that the phoneme is a vowel and operates a consonant length estimation partwhen it judges that the phoneme is a consonant, and when it has judged that this phoneme anteriorly has a closing interval, it operates a closing length estimation part, whereby the respective time lengths are estimated. After that, the estimated time lengths are set by vowel length setting part, consonant length setting partand closing length setting part, respectively.

Speech synthesis device

A speech recognition apparatus is adapted to previously prepare a noise pattern in response to environmental noise prior to inputting a speech signal, evaluate a speech feature vector B.sub.i yielded by subtracting the noise pattern from a feature vector A.sub.i of the input speech upon inputting the speech signal thereafter, spectrum-normalize the speech feature vector B.sub.i, evaluate a local peaks vector by making use of binary-coding processing wherein only a component of a channel being the maximum of the spectrum-normalized vector in a direction of frequency is assumed to be '1', evaluate pattern similarity between an input pattern comprising a local peaks vector from the start point to the end point of the input speech and previously prepared reference patterns of a plurality of categories of the same format as the input pattern, and judge a category of a reference pattern being the maximum among the pattern similarities as a recognized result. As a result, any influence of environmental noise on the speech of concern is eliminated for assuring highly accurate recognition. Furthermore, the speech recognition apparatus is adapted to improve the efficiency and accuracy of speech recognition by evaluating a new speech feature vector of a prescribed frame number by effecting linear expansion therefor on the basis of internal division for adjoining speech feature vectors B.sub.i and B.sub.i +1, and smoothing a local peaks vector.

Speech recognition apparatus for recognizing the category of an input

In a speech recognition system for effecting substantially linear matching, a start point of an input speech pattern is detected to start counting the frames of the input speech pattern for updating a speech frame number. Each time the speech frame number is updated, a plurality of frame numbers of reference templates are generated in substantially a linear relationship to the frame number, thus providing a plurality of matching paths between each of the reference templates and the input speech pattern. The distance between the input pattern data and the reference template data between the corresponding frames specified by each matching path is calculated each time the speech frame number is updated. An accumulated value of the distances along a matching path from the start point of the input speech until a desired speech frame is regarded as a dissimilarity, and the dissimilarity corresponding to each matching path in each reference template is calculated each time the speech frame is updated. The number of the reference template which gives a minimum dissimilarity is detected and stored. At the time of confirming an end of the input speech, the number of the reference template with the minimum dissimilarity is determined to be the recognized result of input speech.

Apparatus and method for recognizing speech

Speech recognition method and system are adapted to previously prepare a noise pattern in response to environmental noise prior to inputting a speech signal, evaluate a speech feature vector Bi yielded by subtracting the noise pattern from a feature vector Ai of the input speech upon inputting the speech signal thereafter, spectrum-normalize the speech feature vector Bi, evaluate a local peaks vector by making use of binary-coding processing wherein only a component of a channel being the maximum of the spectrum-normalized vector in a direction of frequency is assumed to be '1', evaluate pattern similarity between an input pattern comprising a local peaks vector from the start point to the end point of the input speech and previously prepared reference patterns of a plurality of categories of the same format as the input pattern, and judge a category of a reference pattern being the maximum among the pattern similaritites as a recognized result. As a result, any influence of environmental noise on the speech in concern is eliminated for assuring highly accurate recognition. Furthermore, the speech recognition method and system are adapted to improve efficiency and accuracy of speech recognition by making use of processing of evaluating a new speech feature vector of a prescribed frame number of effecting linear expansion therefor on the basis of internal division of adjoining speech feature vectors Bi and Bi+1, and processing of smoothing a local peaks vector.

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Tokyo, Japan

Yukio Tabei