本文選題：維納濾波 + 先驗SNR　； 參考：《計算機應(yīng)用與軟件》2014年11期

【摘要】：提出一種具有較高可懂度的基于維納濾波的語音增強算法。相比于其他語音增強算法,維納濾波法可以明顯提高語音質(zhì)量且含有較少的音樂噪聲,但是它和其他現(xiàn)有語音增強算法一樣,都無法有效提高語音可懂度。因為維納濾波法和其他現(xiàn)有算法都過多注重噪聲減少,卻忽略了SNR(信噪比)的估計誤差和不同的語音幅度譜畸變對可懂度有更重要的影響。為改進這些缺點,此研究依據(jù)于先驗SNR和增益函數(shù)來判定SNR估計誤差和語音畸變區(qū)域,然后對先驗SNR小于-10 d B區(qū)域的增益函數(shù)進行修正,以及幅度譜畸變大于6.02 d B區(qū)域語音進行限制。實驗證明,該算法能有效提升增強后語音可懂度NCM(歸一化協(xié)方差方法)的評測值。
[Abstract]:A speech enhancement algorithm based on Wiener filter with high intelligibility is proposed. Compared with other speech enhancement algorithms, Wiener filter can significantly improve speech quality and contain less music noise, but it can not effectively improve speech intelligibility as other existing speech enhancement algorithms. Because Wiener filter and other existing algorithms pay too much attention to noise reduction, but ignore SNR estimation error and different speech amplitude spectrum distortion have more important influence on intelligibility. In order to improve these shortcomings, this study is based on the prior SNR and gain function to determine the SNR estimation error and the speech distortion region, and then modifies the gain function of the priori SNR less than -10 dB region. And the amplitude spectrum distortion is larger than 6.02 dB. Experimental results show that the proposed algorithm can effectively improve the NCM (normalized covariance method) of speech intelligibility after enhancement.
【作者單位】： 太原理工大學計算機科學與技術(shù)學院;
【基金】：山西省留學歸國人員科研項目(2011-027) 山西省留學人員科技活動擇優(yōu)項目(2011-762)
【分類號】：TN912.35

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相關(guān)期刊論文 前1條

1 張亮;龔衛(wèi)國;;一種改進的維納濾波語音增強算法[J];計算機工程與應(yīng)用;2010年26期

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相關(guān)期刊論文 前5條

1 馬多佳;劉孟美;王e，

本文編號：1934189