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.^^^^
Tipo de documento:
Conferencia
Derechos:
(c) Springer (The original publication is available at www.springerlink.com)
Tots els drets reservats
Citación Bibliográfica:
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