Book chapter
Speech Enhancement Using ICA with EMD-Based Reference
Independent Component Analysis and Blind Signal Separation, pp 739-746
2006
Abstract
Different from the traditional ICA that recovers all the source signals simultaneously, the ICA with reference (ICA-R) extracts only some desired source signals from the mixtures of source signals by incorporating some a priori information into the separation process. This paper applies ICA-R to extracting a target speech signal from its noisy linear mixtures by constructing a proper reference signal with the empirical mode decomposition (EMD). Specifically, EMD is used to obtain an approximate envelope of the power spectrum of the desired speech, which is quite different from the power spectra of the environmental noises. The results of computer simulations and performance analyses demonstrate the efficiency of the proposed method.
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Details
- Title
- Speech Enhancement Using ICA with EMD-Based Reference
- Creators
- Yongrui Zheng - Dalian University of TechnologyQiuhua Lin - Dalian University of TechnologyFuliang Yin - Dalian UniversityHualou Liang - The University of Texas Health Science Center at Houston
- Publication Details
- Independent Component Analysis and Blind Signal Separation, pp 739-746
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000236486300092
- Scopus ID
- 2-s2.0-33745697445
- Other Identifier
- 991019341846704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Theory & Methods