Single-Channel Online Enhancement of Speech Corrupted by Reverberation and Noise
Single-Channel Online Enhancement of Speech Corrupted by Reverberation and Noise
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DOI：
10.1109/taslp.2016.2641904
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发表时间：
2017-03
期刊：
影响因子：
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通讯作者：
Clement S. J. Doire;M. Brookes;P. Naylor;Christopher M. Hicks;Dave Betts;M. Dmour;S. H. Jensen
中科院分区：
文献类型：
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作者：
Clement S. J. Doire;M. Brookes;P. Naylor;Christopher M. Hicks;Dave Betts;M. Dmour;S. H. Jensen
针对混响和噪声对语音质量的影响，提出了一种在线单通道语音增强方法。基于自回归模型的混响功率和隐马尔可夫模型的清洁语音生产，贝叶斯滤波制定的问题，推导出和在线联合估计的声学参数和平均语音，混响，噪声功率在梅尔频带。从这些估计，一个实值的频谱增益推导和频谱增强应用在短时傅里叶变换（STFT）域。该方法产生最先进的性能，并大大降低了混响和噪声的影响，同时提高语音质量，并在具有挑战性的声学环境中保持语音清晰度。
This paper proposes an online single-channel speech enhancement method designed to improve the quality of speech degraded by reverberation and noise. Based on an autoregressive model for the reverberation power and on a hidden Markov model for clean speech production, a Bayesian filtering formulation of the problem is derived and online joint estimation of the acoustic parameters and mean speech, reverberation, and noise powers is obtained in mel-frequency bands. From these estimates, a real-valued spectral gain is derived and spectral enhancement is applied in the short-time Fourier transform (STFT) domain. The method yields state-of-the-art performance and greatly reduces the effects of reverberation and noise while improving speech quality and preserving speech intelligibility in challenging acoustic environments.