基于加权最小统计的噪声谱估计改进算法
doi: 10.3724/SP.J.1146.2008.00467
An Improved Noise Spectral Estimation Algorithm Based on the Weighted Minimum Statistics
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摘要: 针对最小统计的噪声谱估计算法在噪声谱上升时跟踪时延较大的问题，该文给出了一种加权最小统计的噪声谱估计改进算法，通过分析加权对最小统计噪声谱估计算法的影响，采用3种简单典型曲线构造权值，用实验的方法比较得出由余弦曲线构造的权值最优。实验结果表明加权最小统计的噪声谱估计改进算法能够快速跟踪噪声谱的变化，提高了噪声谱估计的准确性，改善了增强后的语音质量。
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关键词:
- 语音增强;噪声谱估计;加权最小统计
Abstract: As the noise spectral estimation based on the minimum statistics introduces significant tracking latency when the noise spectral rises, an improved algorithm based on the weight minimum statistics is presented. Analyzing the influence of weight on the noise spectral estimation based on the minimum statistics, three kinds of typical simple curves are used to compute the weight, and the experiment shows that the weight computed by the cosine curve is the best. The simulation results show that the improved algorithm traces the change of noise spectral quickly in most cases, improves the accuracy of the noise spectral estimation and the quality of speech in the non-stationary noise environment. -
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