Probabilistic Adaptation Mode Control Algorithm for GSC-Based Noise Reduction
Summary :
An efficient noise reduction algorithm is proposed to improve speech recognition performance for human machine interfaces. In the algorithm, a probabilistic adaptation mode controller (AMC) is designed and adopted to the generalized sidelobe canceller (GSC). To detect target speech intervals, the proposed AMC calculates the inter-channel correlation and estimates speech absence probability (SAP). Based on the SAP, the adaptation mode of the adaptive filter in the GSC is decided. Experimental results show the proposed algorithm significantly improves speech recognition performances and signal-to-noise ratios in real noisy environments.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E93-A No.3 pp.627-630
- Publication Date
- 2010/03/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E93.A.627
- Type of Manuscript
- LETTER
- Category
- Speech and Hearing
Authors
Keyword
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Seungho HAN, Jungpyo HONG, Sangbae JEONG, Minsoo HAHN, "Probabilistic Adaptation Mode Control Algorithm for GSC-Based Noise Reduction" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 3, pp. 627-630, March 2010, doi: 10.1587/transfun.E93.A.627.
Abstract: An efficient noise reduction algorithm is proposed to improve speech recognition performance for human machine interfaces. In the algorithm, a probabilistic adaptation mode controller (AMC) is designed and adopted to the generalized sidelobe canceller (GSC). To detect target speech intervals, the proposed AMC calculates the inter-channel correlation and estimates speech absence probability (SAP). Based on the SAP, the adaptation mode of the adaptive filter in the GSC is decided. Experimental results show the proposed algorithm significantly improves speech recognition performances and signal-to-noise ratios in real noisy environments.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.627/_p
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@ARTICLE{e93-a_3_627,
author={Seungho HAN, Jungpyo HONG, Sangbae JEONG, Minsoo HAHN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Probabilistic Adaptation Mode Control Algorithm for GSC-Based Noise Reduction},
year={2010},
volume={E93-A},
number={3},
pages={627-630},
abstract={An efficient noise reduction algorithm is proposed to improve speech recognition performance for human machine interfaces. In the algorithm, a probabilistic adaptation mode controller (AMC) is designed and adopted to the generalized sidelobe canceller (GSC). To detect target speech intervals, the proposed AMC calculates the inter-channel correlation and estimates speech absence probability (SAP). Based on the SAP, the adaptation mode of the adaptive filter in the GSC is decided. Experimental results show the proposed algorithm significantly improves speech recognition performances and signal-to-noise ratios in real noisy environments.},
keywords={},
doi={10.1587/transfun.E93.A.627},
ISSN={1745-1337},
month={March},}
Copy
TY - JOUR
TI - Probabilistic Adaptation Mode Control Algorithm for GSC-Based Noise Reduction
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 627
EP - 630
AU - Seungho HAN
AU - Jungpyo HONG
AU - Sangbae JEONG
AU - Minsoo HAHN
PY - 2010
DO - 10.1587/transfun.E93.A.627
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2010
AB - An efficient noise reduction algorithm is proposed to improve speech recognition performance for human machine interfaces. In the algorithm, a probabilistic adaptation mode controller (AMC) is designed and adopted to the generalized sidelobe canceller (GSC). To detect target speech intervals, the proposed AMC calculates the inter-channel correlation and estimates speech absence probability (SAP). Based on the SAP, the adaptation mode of the adaptive filter in the GSC is decided. Experimental results show the proposed algorithm significantly improves speech recognition performances and signal-to-noise ratios in real noisy environments.
ER -
English
