Probabilistic Adaptation Mode Control Algorithm for GSC-Based Noise Reduction

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概要

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• 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.

• 2010-03-01

著者

• Hahn Minsoo

  Dept. Of Information And Communications Eng. Kaist

• HAN Seungho

  Dept. of Information and Communications Eng., KAIST

• HONG Jungpyo

  Dept. of Information and Communications Eng., KAIST

• JEONG Sangbae

  Dept. of Electronics Eng. (ERI), Gyeongsang National University

• Han Seungho

  Dept. Of Information And Communications Eng. Kaist

• Hong Jungpyo

  Dept. Of Information And Communications Eng. Kaist

• Jeong Sangbae

  Dept. Of Electronics Eng. (eri) Gyeongsang National University

関連論文

• Probabilistic Adaptation Mode Control Algorithm for GSC-Based Noise Reduction

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