Source: http://www.google.com/patents/US5159637?dq=ininventor:oliver+ininventor:steele
Timestamp: 2016-09-26 19:24:08
Document Index: 387301515

Matched Legal Cases: ['ART 122', 'ART 123', 'art 122', 'ART 124', 'ART 125', 'ART 127', 'art 127', 'art 127']

Patent US5159637 - Speech word recognizing apparatus using information indicative of the ... - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsAn isolated speech word recognizer for recognizing an input pattern as one of a plurality of known patterns, comprising a similarity information storing unit for storing similarity information representing the degree of significance of a feature in each of the known patterns for recognizing thereof,...http://www.google.com/patents/US5159637?utm_source=gb-gplus-sharePatent US5159637 - Speech word recognizing apparatus using information indicative of the relative significance of speech featuresAdvanced Patent SearchTry the new Google Patents, with machine-classified Google Scholar results, and Japanese and South Korean patents.Publication numberUS5159637 APublication typeGrantApplication numberUS 07/821,861Publication dateOct 27, 1992Filing dateJan 16, 1992Priority dateJul 27, 1988Fee statusLapsedPublication number07821861, 821861, US 5159637 A, US 5159637A, US-A-5159637, US5159637 A, US5159637AInventorsMakoto Okazaki, Koji EtoOriginal AssigneeFujitsu LimitedExport CitationBiBTeX, EndNote, RefManPatent Citations (8), Referenced by (17), Classifications (4), Legal Events (5) External Links: USPTO, USPTO Assignment, EspacenetSpeech word recognizing apparatus using information indicative of the relative significance of speech features
US 5159637 AAbstract
An isolated speech word recognizer for recognizing an input pattern as one of a plurality of known patterns, comprising a similarity information storing unit for storing similarity information representing the degree of significance of a feature in each of the known patterns for recognizing thereof, and a most similar pattern determining unit for determining one of the plurality of known patterns as the most similar pattern to the input pattern by the use of the similarity information, whereby the recognition performance is improved.
1. An isolated speech word recognizer for recognizing an input pattern as one of a plurality of known patterns, comprising:similarity information storing means for storing similarity information representing the degree of significance of features in each of the known patterns for recognizing the features; and most similar pattern determining means, operatively connected to said similarity information storing means, for determining one of said plurality of known patterns as a most similar pattern to the input pattern by the use of the similarity information, a plurality of input feature parameters and a plurality of reference feature parameters, wherein the similarity information is a plurality of weight patterns respectively corresponding to the plurality of known patterns, each of the weight patterns representing the degree of significance of the features of the known patterns to recognize the most similar pattern, wherein said speech word recognizer further comprises:feature parameter extracting means, operatively connected to said most similar pattern determining means, for extracting the plurality of input feature parameters from the input pattern; and reference pattern storing means, operatively connected to said most similar pattern determining means, for storing a plurality of reference patterns as the known patterns each having a plurality of reference feature parameters, and wherein the weight pattern of each of the reference patterns having a plurality of weight parameters corresponding to the plurality of reference feature parameters in each of the plurality of reference patterns, each of the weight parameters being smaller than a predetermined value when the corresponding reference feature parameter is significant to recognize the reference pattern corresponding thereto, and being larger than the predetermined value when the corresponding reference feature parameter is not significant to recognize the reference pattern corresponding thereto, wherein said most similar pattern determining means comprises:distance calculating means for calculating distances between the input pattern and the plurality of reference patterns; and multiplying means for multiplying the calculated distances by the weight patterns corresponding thereto to obtain weighted distances, and wherein said most similar pattern determining means determines one of the plurality of reference patterns as the most similar pattern to the input pattern by determining a shortest distance from the weighted distances. 2. An isolated speech word recognizer as claimed in claim 1, wherein each of the weighted distances is a sum of weighted differences, each of the weighted differences being obtained by multiplying a difference between the input feature parameter and the corresponding reference feature parameter by the weight parameter corresponding thereto.
Accordingly, an object of the present invention is to provide an isolated speech recognizer in which error recognition due to the fluctuations of the input speech and the like is decreased and the recognition performance is improved.
For better understanding of the present invention, a conventional speech recognizer and problems therein will first be described with reference to FIGS. 1 to 4.
FIG. 5 is a block diagram showing the principle of the first embodiment of the present invention. In the figure, an essential part of an isolated speech word recognizer for recognizing an input pattern 51 of a speech word to be the same as a reference pattern 52 according to the first embodiment of the present invention is illustrated. The speech recognizer comprises a distance calculating unit 53 for calculating distances between an input feature parameter Pin extracted from an input speech signal and a plurality of reference patterns Pkn, and a shortest distance determining unit 58 in the distance calculating unit 53 for determining which one of the reference patterns corresponds to the shortest distance in the distances obtained by the distance calculating unit. The shortest distance determining unit 58 includes, according to the present invention, a weight data multipling unit 55 for multipling weight data 56 by the differences between the feature parameter 50 of the input pattern 51 and the feature parameters 54 of the reference patterns 52 before determining the reference pattern corresponding to the shortest distance. Alternatively, weight data 56 may be multiplied by both the feature parameter 50 of the input pattern 51 and the feature parameters 54 of the reference patterns 52 before determining the reference pattern corresponding to the shortest distance.
In the conventional preselection system, there was a problem in that a plurality of feature patterns are preselected in response to a single speech content. Therefore, in such a case, even when N feature patterns are preselected, the number of the preselected features corresponding to one spoken word becomes smaller than N so that there was a problem of a narrow preselection range.
FEATURE EXTRACTING PART 122
By the use of 12 channel-bandpass filter (BPF), the input speech signal is divided into 12 bands. For each channel, a rectified value, i.e., absolute value smoothed by a lowpass filter, is obtained. Each channel value is output at every 10 milliseconds.
SPEECH INTERVAL DETECTING PART 123
The beginning and the end of the speech interval are found by determining whether the input speech power is higher or lower than a certain threshold level. Then, the data output from the feature extracting part 122 during the detected interval is stored.
NORMALIZATION PROCESSING PART 124
Each of the different speech intervals from the beginnings to the ends are divided into eight sections along the time axis. Then, in each of the divided intervals, averaging is effected. Whereby, 12 channels�8 frams=96 feature parameters are obtained.
DICTIONARY 126
Using learned speech sounds, three feature patterns are formed and recorded for one speech input, by the use of the speech interval detecting part and the normalization processing part.
PRESELECTION PROCESSING PART 125
This portion is a part to which the present invention is applied. The construction is the same as that shown in FIG. 10.
MAIN SELECTION PROCESSING PART 127
From the 10 patterns formed by the preselection processing part 127, one pattern (one speech sound) is selected. The construction is as shown in FIG. 11.
DIALER 129
This receives the speech number output from the main selection processing part 127, and outputs corresponding pulses to the line.
The third embodiment relates to a speech recognizer in which a dictionary for storing feature parameters of speech sounds to be recognized stores a similarity function.
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