The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Um algoritmo eficiente de redução de ruído é proposto para melhorar o desempenho do reconhecimento de fala para interfaces homem-máquina. No algoritmo, um controlador de modo de adaptação probabilístico (AMC) é projetado e adotado para o cancelador de lóbulo lateral generalizado (GSC). Para detectar intervalos de fala alvo, o AMC proposto calcula a correlação entre canais e estima a probabilidade de ausência de fala (SAP). Com base no SAP, é decidido o modo de adaptação do filtro adaptativo no GSC. Resultados experimentais mostram que o algoritmo proposto melhora significativamente o desempenho de reconhecimento de fala e a relação sinal-ruído em ambientes reais com ruído.
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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},}
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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 -