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Speech Enhancement: A Multivariate Empirical Mode Decomposition Approach

Speech Enhancement: A Multivariate Empirical Mode Decomposition Approach
 
Solé-Casals, Jordi ; Gallego Jutglà, Esteve ; Martí i Puig, Pere ; Travieso, Carlos M. ; Alonso, Jesús B.
2013

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Abstract

Speech signals in real scenario ambient are usually mixed with some other signals, such as noise. This may interfere with posterior signal processing applied to the signals. In this work, a new technique of data denoising is presented using multivariate Empirical Mode Decomposition. Different SNR ratios are tested in order to ...»»»»
Speech signals in real scenario ambient are usually mixed with some other signals, such as noise. This may interfere with posterior signal processing applied to the signals. In this work, a new technique of data denoising is presented using multivariate Empirical Mode Decomposition. Different SNR ratios are tested in order to study the evolution of the improvement of the recovered data. An improvement of the analyzed data is obtained with all the SNR levels tested.^^^^

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Conference object

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(c) Springer (The original publication is available at www.springerlink.com)
 
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Citation:

Jordi Solé-Casals, Esteve Gallego-Jutglà, Pere Martí-Puig, Carlos M. Travieso, and Jesús B. Alonso (2013). "Speech Enhancement: A Multivariate Empirical Mode Decomposition Approach" A: Lecture Notes in Computer Science, 7911 LNAI, pp. 192-199