Research on Noise Reduction Algorithm Based on Combination of LMS Filter and Spectral Subtraction
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초록
In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithmand music noise problem of spectral subtraction algorithm during the speech signal processing, we combinethese two algorithms and propose one novel noise reduction method, showing a strong performance on par oreven better than state of the art methods. We first use the least mean square algorithm to reduce the averageintensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experimentsprove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomesshortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noiseratio of original speech data and improves the final noise reduction performance.
Abstract
In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithmand music noise problem of spectral subtraction algorithm during the speech signal processing, we combinethese two algorithms and propose one novel noise reduction method, showing a strong performance on par oreven better than state of the art methods. We first use the least mean square algorithm to reduce the averageintensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experimentsprove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomesshortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noiseratio of original speech data and improves the final noise reduction performance.
참고문헌 (15)
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