Combining frequency warping and spectral shaping in HMM based sp

Details Combining frequency warping and spectral shaping in HMM based sp Combining frequency warping and spectral shaping in HMM based sp

1997-03-20

1999-07-27

Hudspeth, David R.

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

G10L 302

Patent

active

059307536

ABSTRACT:
Frequency warping approaches to speaker normalization have been proposed and evaluated on various speech recognition tasks. In all cases, frequency warping was found to significantly improve recognition performance by reducing the mismatch between test utterances presented to the recognizer and the speaker independent HMM model. This invention relates to a procedure which compensates utterances by simultaneously scaling the frequency axis and reshaping the spectral energy contour. This procedure is shown to reduce the error rate in a telephone based connected digit recognition task by 30%.

REFERENCES:
"An Approach to Speaker Adaptation Based on Analytic Functions" by McDonough et al., pp. 721-724 (1995).
"Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models" by Leggetter et al., pp. 171-185 (1995).
"Unsupervised Speaker Adaptation by Probabilistic Spectrum Fitting" by Cox et al. (1989).
"N-Best-Based Instantaneous Speaker Adaptation Method for Speech Recognition" by Matsui et al., pp. 973-976 (1996).
Speaker Normalization Using Efficient Frequency Warping Procedures by Lee et al. (1996).
Rose et al. A User Configurable Ssytem for Voice Label Recognition. 582-585.
Potamianos et al. On combining freequency warping and spectral shaping in HMM based speech. 1275-1278, 1997.

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