Subband-based blind signal separation for noisy speech recognition

Hyung Min Park; Ho Young Jung; Te Won Lee; Soo Young Lee

doi:10.1049/el:19991358

Subband-based blind signal separation for noisy speech recognition

Hyung Min Park
, Ho Young Jung
, Te Won Lee
, Soo Young Lee

School of Electronics Engineering

Korea Advanced Institute of Science and Technology
Salk Institute for Biological Studies
University of California at San Diego

Research output: Contribution to journal › Article › peer-review

45 Scopus citations

Abstract

A method for directly extracting clean speech features from noisy speech is proposed. This process is based on independent component analysis (ICA) and a new feature analysis technique for reducing the computational complexity of the frequency-domain ICA. For noisy speech signals recorded in real environments, this method yielded a considerable performance improvement.

Original language	English
Pages (from-to)	2011-2012
Number of pages	2
Journal	Electronics Letters
Volume	35
Issue number	23
DOIs	https://doi.org/10.1049/el:19991358
State	Published - 11 Nov 1999

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10.1049/el:19991358

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title = "Subband-based blind signal separation for noisy speech recognition",

abstract = "A method for directly extracting clean speech features from noisy speech is proposed. This process is based on independent component analysis (ICA) and a new feature analysis technique for reducing the computational complexity of the frequency-domain ICA. For noisy speech signals recorded in real environments, this method yielded a considerable performance improvement.",

author = "Park, \{Hyung Min\} and Jung, \{Ho Young\} and Lee, \{Te Won\} and Lee, \{Soo Young\}",

year = "1999",

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AU - Park, Hyung Min

AU - Jung, Ho Young

AU - Lee, Te Won

AU - Lee, Soo Young

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N2 - A method for directly extracting clean speech features from noisy speech is proposed. This process is based on independent component analysis (ICA) and a new feature analysis technique for reducing the computational complexity of the frequency-domain ICA. For noisy speech signals recorded in real environments, this method yielded a considerable performance improvement.

AB - A method for directly extracting clean speech features from noisy speech is proposed. This process is based on independent component analysis (ICA) and a new feature analysis technique for reducing the computational complexity of the frequency-domain ICA. For noisy speech signals recorded in real environments, this method yielded a considerable performance improvement.

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DO - 10.1049/el:19991358

M3 - Article

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SN - 0013-5194

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EP - 2012

JO - Electronics Letters

JF - Electronics Letters

IS - 23

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Subband-based blind signal separation for noisy speech recognition

Abstract

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