An investigation of speech enhancement using wavelet filtering method
An investigation of speech enhancement using wavelet filtering method
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DOI：
10.1007/s10772-010-9073-1
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发表时间：
2010-05
影响因子：
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通讯作者：
K. Daqrouq;I. Abu-Isbeih;O. Daoud;Emad Khalaf
中科院分区：
文献类型：
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作者：
K. Daqrouq;I. Abu-Isbeih;O. Daoud;Emad Khalaf
本文研究了用反向双正交小波（RBW）对语音信号的高、低通频带进行多阶段卷积的小波滤波器的应用。将语音信号分解为两个频带；然后通过小波滤波器在不同阶段分别去除每个波段的噪声。这种方法提供了更好的结果，因为它不会切断语音信息，而使用传统的阈值会发生这种情况。我们通过几个噪声概率分布函数对该方法进行了测试。主观评价与客观评价相结合，实现最优的调查方法。该方法简单，但却有令人惊讶的高质量结果。该方法优于Donoho和Johnstone阈值方法和Birge-Massart阈值策略方法。
This paper investigates the utilization of wavelet filters via multistage convolution by Reverse Biorthogonal Wavelets (RBW) in high and low pass band frequency parts of speech signal. Speech signal is decomposed into two pass bands of frequency; high and low, and then the noise is removed in each band individually in different stages via wavelet filters. This approach provides better outcomes because it does not cut the speech information, which occurs when utilizing conventional thresholding. We tested the proposed method via several noise probability distribution functions. Subjective evaluation is engaged in conjunction with objective evaluation to accomplish optimal investigation method. The method is simple but has surprise high quality results. The method shows superiority over Donoho and Johnstone thresholding method and Birge-Massart thresholding strategy method.