Speech Enhancement: A Multivariate Empirical Mode Decomposition Approach
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Author
Other authors
Publication date
2013ISSN
0302-9743
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 study the evolution of the improvement of the recovered
data. An improvement of the analyzed data is obtained with all the SNR levels
tested.
Document Type
Object of conference
Language
English
Keywords
Pages
8 p.
Publisher
Springer
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
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- Documents de Congressos [174]
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