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1 February 1994 Nonlinear techniques for parameter extraction from quasi-continuous wavelet transform with application to speech
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Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172510
Event: Substance Identification Technologies, 1993, Innsbruck, Austria
Abstract
Speaker identification and word spotting will shortly play a key role in a lot of different fields. This paper presents an approach, based on the wavelet transform, to extract features from a speech signal. These features are based on the `modulation model'. An adequate choice of the extracted features dramatically increases the efficiency of the classification performed on the different speakers or on the different words.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephane Maes "Nonlinear techniques for parameter extraction from quasi-continuous wavelet transform with application to speech", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); https://doi.org/10.1117/12.172510
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