Improvements in scale-transform-based features for speech analysis

Srinivasan Umesh; Leon Cohen; Douglas J. Nelson

doi:10.1117/12.292805

30 October 1997 Improvements in scale-transform-based features for speech analysis

Srinivasan Umesh, Leon Cohen, Douglas J. Nelson

Author Affiliations +

Proceedings Volume 3169, Wavelet Applications in Signal and Image Processing V; (1997) https://doi.org/10.1117/12.292805
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

In this paper, we present improvements over the original scale-cepstrum proposed. The scale-cepstrum was proposed as an acoustic feature for speech analysis and was motivated by a desire to normalize the first-order effects of differences in vocal-tract lengths for a given vowel. Our subsequent work has shown that a more appropriate frequency-warping than the log-warping used is necessary to account for the frequency dependency of the scale-factor. Using this more appropriate frequency-warping and a modified method of computing the scale-cepstrum we have obtained improved features that provide better separability between vowels than before, and are also robust to noise. We have used the generalized F-ratio test as a measure of separability and have compared the proposed improved features with the melcepstral features. The data used in the comparison consist of ten vowels extracted from sentences spoken by different speakers in the TIMIT database.

Citation Download Citation

Srinivasan Umesh, Leon Cohen, and Douglas J. Nelson "Improvements in scale-transform-based features for speech analysis", Proc. SPIE 3169, Wavelet Applications in Signal and Image Processing V, (30 October 1997); https://doi.org/10.1117/12.292805

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