System and method of mu-law or A-law compression of bark amplitudes for speech recognition
First Claim
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1. A voice recognizer of a distributed voice recognition system, comprising:
- a bark amplitude generation module configured to convert a digitized speech signal to bark amplitudes;
a mu-log compression module coupled to the bark amplitude generation module, the mu-log compression module configured to perform mu-log compression of the bark amplitudes;
a RASTA filtering module coupled to the mu-log compression module, the RASTA filtering module configured to RASTA filter the mu-log bark amplitudes; and
a cepstral transformation module coupled to the RASTA filtering module, the cepstral transformation module configured to generate j static cepstral coefficients and j dynamic cepstral coefficients.
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Abstract
A method and system that improves voice recognition by improving the voice recognizer of a voice recognition system. Mu-law compression of bark amplitudes is used to reduce the effect of additive noise and thus improve the accuracy of the voice recognition system. A-law compression of bark amplitudes is used to improve the accuracy of the voice recognizer. Both mu-law compression and mu-law expansion can be used in the voice recognizer to improve the accuracy of the voice recognizer. Both A-law compression and A-law expansion can be used in the voice recognizer to improve the accuracy of the voice recognizer.
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Citations
54 Claims
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1. A voice recognizer of a distributed voice recognition system, comprising:
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a bark amplitude generation module configured to convert a digitized speech signal to bark amplitudes;
a mu-log compression module coupled to the bark amplitude generation module, the mu-log compression module configured to perform mu-log compression of the bark amplitudes;
a RASTA filtering module coupled to the mu-log compression module, the RASTA filtering module configured to RASTA filter the mu-log bark amplitudes; and
a cepstral transformation module coupled to the RASTA filtering module, the cepstral transformation module configured to generate j static cepstral coefficients and j dynamic cepstral coefficients. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A voice recognizer of a distributed voice recognition system, comprising:
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a bark amplitude generation module configured to convert a digitized speech signal to bark amplitudes;
an A-log compression module coupled to the bark amplitude generation module, the A-log compression module configured to perform A-log compression of the bark amplitudes;
a RASTA filtering module coupled to the A-log compression module, the RASTA filtering module configured to RASTA filter the A-log bark amplitudes; and
a cepstral transformation module coupled to the RASTA filtering module, the cepstral transformation module configured to generate j static cepstral coefficients and j dynamic cepstral coefficients. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A voice recognizer of a distributed voice recognition system, comprising:
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a bark amplitude generation module configured to converts a digitized speech signal to bark amplitudes;
a mu-log compression module coupled to the bark amplitude generation module, the mu-log compression module configured to perform mu-log compression of the bark amplitudes;
a RASTA filtering module coupled to the mu-log compression module, the RASTA filtering module configured to RASTA filters the mu-log bark amplitudes; and
a mu-log expansion module coupled to the RASTA filtering module, the mu-log expansion module configured to perform mu-log expansion of the filtered mu-log bark amplitudes. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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22. A voice recognizer of a distributed voice recognition system, comprising:
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a bark amplitude generation module configured to convert a digitized speech signal to bark amplitudes;
an A-log compression module coupled to the bark amplitude generation module, the A-log compression module configured to perform A-log compression of the bark amplitudes;
a RASTA filtering module coupled to the A-log compression module, the RASTA filtering module configured to RASTA filter the A-log bark amplitudes; and
an A-log expansion module coupled to the RASTA filtering module, the A-log expansion module configured to perform A-log expansion of the filtered A-log bark amplitudes. - View Dependent Claims (23, 24, 25, 26, 27, 28)
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29. A method of voice recognizer processing for voice recognition, comprising:
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converting a digitized speech signal to bark amplitudes;
mu-log compressing the bark amplitudes;
RASTA-filtering the mu-log bark amplitudes; and
transforming cepstrally the mu-log bark amplitudes to j static cepstral coefficients and j dynamic cepstral coefficients. - View Dependent Claims (30, 31, 32, 33, 34)
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35. A method of voice recognition, comprising:
- converting a digitized speech signal to bark amplitudes;
mu-log compressing the bark amplitudes;
RASTA-filtering the mu-log bark amplitudes;
transforming cepstrally the mu-log bark amplitudes to j static cepstral coefficients and j dynamic cepstral coefficients; and
producing a recognition hypothesis based on the j static cepstral coefficients and j dynamic cepstral coefficients.
- converting a digitized speech signal to bark amplitudes;
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36. A method of voice recognition, comprising:
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converting a digitized speech signal to bark amplitudes;
A-log compressing the bark amplitudes;
RASTA-filtering the A-log bark amplitudes; and
transforming cepstrally the A-log bark amplitudes to j static cepstral coefficients and j dynamic cepstral coefficients. - View Dependent Claims (37, 38, 39, 40, 41)
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42. A method of voice recognition, comprising:
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converting a digitized speech signal to bark amplitudes;
A-log compressing the bark amplitudes;
RASTA-filtering the A-log bark amplitudes;
transforming cepstrally the A-log bark amplitudes to j static cepstral coefficients and j dynamic cepstral coefficients; and
producing a recognition hypothesis based on the j static cepstral coefficients and j dynamic cepstral coefficients.
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43. A method of voice recognition, comprising:
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converting a digitized speech signal to bark amplitudes;
mu-log compressing the bark amplitudes;
RASTA-filtering the mu-log bark amplitudes; and
mu-log expanding the filtered mu-log bark amplitudes. - View Dependent Claims (44, 45, 46, 47)
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48. A method of voice recognition, comprising:
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converting a digitized speech signal to bark amplitudes;
mu-log compressing the bark amplitudes;
RASTA-filtering the mu-log bark amplitudes; and
mu-log expanding the filtered mu-log bark amplitudes; and
producing a recognition hypothesis based on the expanded mu-log bark amplitudes.
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49. A method of voice recognition, comprising:
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converting a digitized speech signal to bark amplitudes;
A-log compressing the bark amplitudes;
RASTA-filtering the A-log bark amplitudes; and
A-log expanding the filtered A-log bark amplitudes. - View Dependent Claims (50, 51, 52, 53)
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54. A method of voice recognition, comprising:
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converting a digitized speech signal to bark amplitudes;
A-log compressing the bark amplitudes;
RASTA-filtering the A-log bark amplitudes; and
A-log expanding the filtered A-log bark amplitudes; and
producing a recognition hypothesis based on the expanded A-log bark amplitudes.
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Specification