A Model-Based Soft Decision Approach for Speech Enhancement

作者：Wang, Xianyun; Bao, Changchun^*; Bao, Feng

来源：China Communications, 2017, 14(9): 11-22.

DOI：10.1109/cc.2017.8068760

• speech enhancement
• soft masks
• CASA
• threshold

Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision (termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of the problem, a soft decision is often used as an optimal technique for speech restoration. In this paper, considering a new fashion of speech and noise models, we present two model-based soft decision techniques. One technique estimates a ratio mask generated by the exact Bayesian estimators of speech and noise. For the second technique, we consider one issue that an optimum local criterion (LC) for a certain SNR may not be appropriate for other SNRs. So we estimate a probabilistic mask with a variable LC. Experimental results show that the proposed method achieves a better performance than reference methods in speech quality.

• 出版日期2017-9
• 单位北京工业大学