Voice recognition using an eigenvector
First Claim
1. A voice recognition method including the steps of:
- (a) forming an input voice pattern from an input voice signal of an unknown input voice, said input voice pattern including a plurality of frames, each frame having frequency and time data;
(b) comparing less than all of said frequency and time data of said input voice pattern with a library of known voice patterns, each of said known voice patterns having its own frequency and time data, to select a plurality of candidate voice patterns, each of said candidate voice patterns having;
(1) an eigenvector having a non-zero minimum eigenvalue; and
(2) an inner product frequency distribution of inner products between (i) the frames of each of said candidate voice patterns and (ii) said eigenvector;
(c) calculating an inner product frequency distribution of inner products between the frames of said input voice pattern and the eigenvector of each of said plurality of candidate voice patterns; and
(d) selecting one of said plurality of candidate voice patterns, whose inner product frequency distribution is most similar to one of said calculated inner product frequency distributions calculated at said calculating step to thereby identify said input voice by the thus selected candidate voice pattern.
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Abstract
A voice pattern in the form of a matrix and comprised of a plurality of frames, each including time-spectral information and temporal information, is formed from an unknown input voice signal. The voice pattern is compared with each of the voice patterns of a library of known voices partly to select a plurality of candidate voices. Each of the library voices has a predetermined eigenvector and an inner product frequency distribution of inner products between the eigenvector and the frames of its voice pattern. Then, inner products between the voice pattern of the input voice signal and the eigenvector of each of the candidate library voice are calculated. One of the plurality of candidate library voices whose predetermined inner product frequency distribution is most similar to one of the thus calculated inner product frequency distributions is selected to identify the input voice signal.
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Citations
4 Claims
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1. A voice recognition method including the steps of:
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(a) forming an input voice pattern from an input voice signal of an unknown input voice, said input voice pattern including a plurality of frames, each frame having frequency and time data; (b) comparing less than all of said frequency and time data of said input voice pattern with a library of known voice patterns, each of said known voice patterns having its own frequency and time data, to select a plurality of candidate voice patterns, each of said candidate voice patterns having; (1) an eigenvector having a non-zero minimum eigenvalue; and (2) an inner product frequency distribution of inner products between (i) the frames of each of said candidate voice patterns and (ii) said eigenvector; (c) calculating an inner product frequency distribution of inner products between the frames of said input voice pattern and the eigenvector of each of said plurality of candidate voice patterns; and (d) selecting one of said plurality of candidate voice patterns, whose inner product frequency distribution is most similar to one of said calculated inner product frequency distributions calculated at said calculating step to thereby identify said input voice by the thus selected candidate voice pattern. - View Dependent Claims (2, 3, 4)
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Specification