Investigation on LP-residual representations for speaker identification
Pattern Recognition
Pitch determination of noisy speech using higher order statistics
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Applications of cumulants in speech processing
NOLISP'09 Proceedings of the 2009 international conference on Advances in Nonlinear Speech Processing
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The use of cumulant-based LP (linear prediction) analysis for speech recognition in the presence of noise is proposed. This method assumes the speech signal to be non-Gaussian. It is shown that cepstral coefficients derived by this method are quite insensitive to additive Gaussian noise which can be white or colored. The performance of a recognizer based on these estimates is compared to the performance of one that uses LP estimates derived from the autocorrelation function. It is found that at low SNR (below about 20 dB) the cumulant-based estimates outperform the autocorrelation-based estimates. At higher SNRs the reverse is true. The reasons for this behavior are not yet understood. However, it is shown that, by combining the two estimates, one can achieve recognition accuracy that is better than that of the conventional recognizer at all SNRs.