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Body-conducted speech retrieval from a noisy environment using differential acceleration

Body-conducted speech retrieval from a noisy environment using differential acceleration Speech recognition tends to be influenced by noise in the air. Body-conducted speech offers a robust signal extraction method from noisy environments, particularly because body-conducted speech is a propagated sound and not easily influenced by noise. However, when body-conducted speech is extracted with an accelerator, the typical frequency component of 2 kHz or more decreases compared with normal speech. Thus, we investigated a technique combining differential acceleration and noise reduction to estimate a clear signal using only body-conducted speech from a noisy room. The recognition rate confirmed about 3-4% is improved with proposed method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Advanced Mechatronic Systems Inderscience Publishers

Body-conducted speech retrieval from a noisy environment using differential acceleration

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1756-8412
eISSN
1756-8420
DOI
10.1504/IJAMechS.2010.033597
Publisher site
See Article on Publisher Site

Abstract

Speech recognition tends to be influenced by noise in the air. Body-conducted speech offers a robust signal extraction method from noisy environments, particularly because body-conducted speech is a propagated sound and not easily influenced by noise. However, when body-conducted speech is extracted with an accelerator, the typical frequency component of 2 kHz or more decreases compared with normal speech. Thus, we investigated a technique combining differential acceleration and noise reduction to estimate a clear signal using only body-conducted speech from a noisy room. The recognition rate confirmed about 3-4% is improved with proposed method.

Journal

International Journal of Advanced Mechatronic SystemsInderscience Publishers

Published: Jan 1, 2010

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