Adaptive Noise Suppression Algorithm for Speech Signal Based on Stochastic System Theory
Summary :
Numerous noise suppression methods for speech signals have been developed up to now. In this paper, a new method to suppress noise in speech signals is proposed, which requires a single microphone only and doesn't need any priori-information on both noise spectrum and pitch. It works in the presence of noise with high amplitude and unknown direction of arrival. More specifically, an adaptive noise suppression algorithm applicable to real-life speech recognition is proposed without assuming the Gaussian white noise, which performs effectively even though the noise statistics and the fluctuation form of speech signal are unknown. The effectiveness of the proposed method is confirmed by applying it to real speech signals contaminated by noises.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E94-A No.8 pp.1618-1627
- Publication Date
- 2011/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E94.A.1618
- Type of Manuscript
- Special Section PAPER (Special Section on Advances in Adaptive Signal Processing and Applications)
- Category
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Akira IKUTA, Hisako ORIMOTO, "Adaptive Noise Suppression Algorithm for Speech Signal Based on Stochastic System Theory" in IEICE TRANSACTIONS on Fundamentals,
vol. E94-A, no. 8, pp. 1618-1627, August 2011, doi: 10.1587/transfun.E94.A.1618.
Abstract: Numerous noise suppression methods for speech signals have been developed up to now. In this paper, a new method to suppress noise in speech signals is proposed, which requires a single microphone only and doesn't need any priori-information on both noise spectrum and pitch. It works in the presence of noise with high amplitude and unknown direction of arrival. More specifically, an adaptive noise suppression algorithm applicable to real-life speech recognition is proposed without assuming the Gaussian white noise, which performs effectively even though the noise statistics and the fluctuation form of speech signal are unknown. The effectiveness of the proposed method is confirmed by applying it to real speech signals contaminated by noises.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E94.A.1618/_p
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@ARTICLE{e94-a_8_1618,
author={Akira IKUTA, Hisako ORIMOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Adaptive Noise Suppression Algorithm for Speech Signal Based on Stochastic System Theory},
year={2011},
volume={E94-A},
number={8},
pages={1618-1627},
abstract={Numerous noise suppression methods for speech signals have been developed up to now. In this paper, a new method to suppress noise in speech signals is proposed, which requires a single microphone only and doesn't need any priori-information on both noise spectrum and pitch. It works in the presence of noise with high amplitude and unknown direction of arrival. More specifically, an adaptive noise suppression algorithm applicable to real-life speech recognition is proposed without assuming the Gaussian white noise, which performs effectively even though the noise statistics and the fluctuation form of speech signal are unknown. The effectiveness of the proposed method is confirmed by applying it to real speech signals contaminated by noises.},
keywords={},
doi={10.1587/transfun.E94.A.1618},
ISSN={1745-1337},
month={August},}
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TY - JOUR
TI - Adaptive Noise Suppression Algorithm for Speech Signal Based on Stochastic System Theory
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1618
EP - 1627
AU - Akira IKUTA
AU - Hisako ORIMOTO
PY - 2011
DO - 10.1587/transfun.E94.A.1618
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E94-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2011
AB - Numerous noise suppression methods for speech signals have been developed up to now. In this paper, a new method to suppress noise in speech signals is proposed, which requires a single microphone only and doesn't need any priori-information on both noise spectrum and pitch. It works in the presence of noise with high amplitude and unknown direction of arrival. More specifically, an adaptive noise suppression algorithm applicable to real-life speech recognition is proposed without assuming the Gaussian white noise, which performs effectively even though the noise statistics and the fluctuation form of speech signal are unknown. The effectiveness of the proposed method is confirmed by applying it to real speech signals contaminated by noises.
ER -
English
