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清华大学学报(自然科学版)  2016, Vol. 56 Issue (11): 1173-1178    DOI: 10.16511/j.cnki.qhdxxb.2016.26.007
  电子工程 本期目录 | 过刊浏览 | 高级检索 |
一种改善言语清晰度的子带自适应降噪算法
梁维谦1, 郑方2, 郑佳春1, 朴志刚3
1. 集美大学 信息工程学院, 海上通信与智能电子系统福建省高等学校重点实验室, 厦门 361021;
2. 清华大学 信息技术研究院, 语音和语言技术中心, 北京 100084;
3. 厦门莱亚特医疗器械有限公司, 厦门 361009
Sub-band adaptive noise reduction algorithm to improve speech intelligibility
LIANG Weiqian1, ZHENG Fang2, ZHENG Jiachun1, PIAO Zhigang3
1. Key Laboratory of Maritime Communication and Intelligent Electronic Systems of Fujian Province, College of Information Engineering, Jimei University, Xiamen 361021, China;
2. Center for Speech and Language Technologies, Research Institute of Information Technology, Tsinghua University, Beijing 100084, China;
3. Xiamen LA and Associates Medical Equipment Co., Ltd., Xiamen 361009, China
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摘要 助听器对声音进行压缩放大,需要高言语清晰度的降噪算法。该文提出了一种子带自适应噪声抑制方法,通过加权重叠相加滤波器组和基于心理声学模型的子带划分、基于先验和后验信噪比的快变的非线性降噪增益、基于噪声声压级估值的慢变的增益下限阈值、基于峰值跟踪的子带增益平滑及其跟踪和释放时间系数的精细选择等算法,明显提高了言语清晰度。主观测听实验表明:该方法对输入的不同信噪比的带噪语音的言语清晰度提高约12%~45%。在EZAIRO5900数字信号处理器上实现了此方法,通过对增益公式的量化处理使得整个算法的运行效率提高约30%。
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梁维谦
郑方
郑佳春
朴志刚
关键词 噪声抑制子带非线性增益言语清晰度    
Abstract:Noise reduction algorithms to improve speech intelligibility are needed when sounds are compressed and amplified in hearing aids. A sub-band adaptive noise reduction algorithm was developed with a weighted overlap-add filter bank and psycho-acoustic model for the sub-band splitting. The non-linear noise reduction gains are computed with an estimated a posteriori signal to noise ratio (SNR) and an a priori SNR. The gain floors are determined based on the estimated noise level expressed as the dB sound pressure level (SPL). The final gains are smoothed between the frames by a peak detector with carefully selected attack and release time constants. Listening tests show 12% to 45% improvements in intelligibility by this algorithm for noise corrupted speech. A quantified gain table is also used to replace the non-linear gain computing when the algorithm is implemented on the EZAIRO5900 digital signal processor, with the execution cycle reduced by about 30%.
Key wordsnoise reduction    sub-band    non-linear gains    speech intelligibility
收稿日期: 2016-05-11      出版日期: 2016-11-26
ZTFLH:  TN912.35  
引用本文:   
梁维谦, 郑方, 郑佳春, 朴志刚. 一种改善言语清晰度的子带自适应降噪算法[J]. 清华大学学报(自然科学版), 2016, 56(11): 1173-1178.
LIANG Weiqian, ZHENG Fang, ZHENG Jiachun, PIAO Zhigang. Sub-band adaptive noise reduction algorithm to improve speech intelligibility. Journal of Tsinghua University(Science and Technology), 2016, 56(11): 1173-1178.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2016.26.007  或          http://jst.tsinghuajournals.com/CN/Y2016/V56/I11/1173
  图1 子带降噪算法框图
  图2 降噪增益计算的流程图
  图3 式(7)降噪增益的三维图
  图4 先验信噪比ξ(n,k)=0时,式(7)降噪增益与线性增益的对比
  图5 降噪增益下限阈值?F(k)与噪声声压级PN(n,k)的函数关系
  图6 4种算法对言语清晰度的影响对比
  图7 本文方法中不同增益计算方法对言语清晰度的影响对比
  图8 本文方法中不同频带划分对言语清晰度的影响对比
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