Optimal Noise Estimation under Speech Presence Uncertainty using Minimum Statistics Method

摘要：

Frequency domain speech enhancement algorithm used in the single-microphone mobile phone usually needs a noise estimator. Minimum Statistics Method can track noise robustly. However, many algorithms based on minimum statistics method do not optimize their tracking factor. In this paper, we derive a new global optimal noise tracking factor controlled by another two new parameters. By combining with speech presence uncertainty and minimizing the conditional mean square error, we obtain a global adaptive factor that does not require error monitor, and then we integrate it with minimum statistics method to estimate noise. Finally, the proposed algorithm is evaluated by using it in Log-Spectral Noise Suppressor and results show a better performance.

关键词： speech enhancement single mircophone noise estimation minimum statistics method optimal smoothing factor speech presence uncertainty

作者: Xie danhui Liu guangjun Zhang weibin Xu yunfeng

作者单位: Signal and Information ProcessingThe First Research Institute of Telecom TechnologyShanghai, China Signal and Information Processing The First Research Institute of Telecom Technology Shanghai, China

会议类型: 国际会议

会议名称: 2010 3rd International Conference on Advanced Computer Theory and Engineering(2010年第三届先进计算机理论与工程国际会议 ICACTE 2010)

会议地点: 成都

会议语种:英文

页码: 1-5

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）