This paper proposes a new speech enhancement (SE) algorithm utilizing constraints to the Wiener gain function which is capable of working at 10 dB and lower signal-to-noise ratios (SNRs). The wavelet thresholded multitaper spectrum was taken as the clean spectrum for the constraints. The proposed algorithm was evaluated under eight types of noises and seven SNR levels in NOIZEUS database and was predicted by the composite measures and the SNRLOSS measure to improve subjective quality and speech intelligibility in various noisy environments. Comparisons with two other algorithms (KLT and wavelet thresholding (WT)) demonstrate that in terms of signal distortion, overall quality, and the SNRLOSS measure, our proposed constrained SE algorithm outperforms the KLT and WT schemes for most conditions considered.
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机译：本文提出了一种新的语音增强（SE）算法，该算法利用了对Wiener增益函数的约束，该算法能够工作在10 dB和更低的信噪比（SNR）下。将小波阈值多锥谱作为约束的纯谱。该算法在NOIZEUS数据库的8种噪声和7种SNR级别下进行了评估，并通过复合测量和SNR LOSS 措施进行了预测，以提高各种嘈杂环境中的主观质量和语音清晰度。与其他两种算法（KLT和小波阈值（WT））的比较表明，就信号失真，整体质量和SNR LOSS 度量而言，我们提出的约束SE算法在性能上优于KLT和WT方案。考虑大多数条件。
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