【摘要】：隨著信息社會的飛速發(fā)展,智能手機以及人機語音對話設備得到了廣泛應用,從而語音信號受到越來越多的關注。然而語音信號在產(chǎn)生、傳輸、處理、接收的過程中不可避免因為周圍環(huán)境和傳輸介質的影響而受到噪聲的污染。污染嚴重的情況下會影響語音信號的質量和可懂度,導致人或者接收語音的設備無法聽懂語音。因此,需要利用語音增強技術從帶噪語音信號中分離出原始純凈的語音信號,濾除噪聲。傳統(tǒng)的語音增強方法都從語音質量方向入手,使增強后的語音具有較高信噪比。但是和帶噪語音相比,增強語音的可懂度沒有得到有效提高。這是由于傳統(tǒng)增強算法在濾除噪聲的同時也會濾除有用的語音信號,造成語音畸變失真。 由于維納濾波可以明顯提高語音質量且使增強后語音含有較少音樂噪聲,本文在維納濾波算法的基礎上提出一種具有較高可懂度的改進算法,旨在提高增強后語音的可懂度,使增強后的語音信號更容易被人或者語音設備聽懂理解。 本文首先介紹了語音信號的常識、人的聽覺特性以及噪聲信號的特征,然后系統(tǒng)的講述了四大類語音增強算法�？偨Y了對于增強語音進行評價的相關方法,包括主觀測聽評價方法,語音質量客觀評價方法和語音可懂度客觀評價方法。 根據(jù)維納濾波的推導過程,得到維納濾波器的增益函數(shù)。之后詳細介紹了基于先驗信噪比估計的維納濾波方法,此方法計算過程簡單,且增強后語音的質量提升明顯。通過對句子和輔音語料實驗仿真得到此方法雖然提高語音質量,但沒有真正意義上提高增強后語音的可懂度。分析增強語音未提高語音可懂度的原因,并從剩余信噪比出發(fā)研究得到增強語音幅度譜中存在衰減畸變和放大畸變,且幅度譜大于6.02dB的放大畸變會嚴重影響增強語音的可懂度。通過實驗把原始純凈語音的幅度譜和增強語音的幅度譜進行對比,去掉幅度譜大于6.02dB的畸變區(qū)域,增強語音的可懂度和質量相比帶噪語音得到明顯提升。 在現(xiàn)實處理語音的環(huán)境中不可能有純凈語音,這就需要通過對先驗信噪比進行改進。修正先驗信噪比小于-10dB區(qū)域進而修正濾波算法的增益函數(shù),然后通過已有條件判定幅度譜大于6.02dB區(qū)域,并對此區(qū)域進行約束限制,最終得到具有高可懂度的改進維納濾波增強算法。通過對句子和輔音語料的實驗仿真證實改進的算法確實提高了增強后語音的可懂度。
[Abstract]:With the rapid development of the information society, smart phones and man-machine voice dialogue devices have been widely used, so more and more attention has been paid to speech signals. However, in the process of producing, transmitting, processing and receiving speech signals, it is inevitable to be polluted by noise due to the influence of surrounding environment and transmission medium. The serious pollution will affect the quality and intelligibility of the speech signal, resulting in the person or the receiving device can not understand the speech. Therefore, it is necessary to use speech enhancement technology to separate the original pure speech signal from the noisy speech signal and filter the noise. The traditional speech enhancement methods all start from the aspect of speech quality, which makes the enhanced speech have higher SNR. However, compared with noisy speech, the intelligibility of enhanced speech is not improved effectively. This is because the traditional enhancement algorithm not only filters the noise but also filters the useful speech signal which results in the distortion of the speech. Since Wiener filter can obviously improve the speech quality and make the enhanced speech contain less music noise, this paper proposes an improved algorithm with higher intelligibility based on the Wiener filtering algorithm, which aims to improve the intelligibility of enhanced speech. Make enhanced speech signals easier to understand or understood by people or speech devices. This paper first introduces the common sense of speech signal, human auditory characteristics and the characteristics of noise signal, and then systematically describes four kinds of speech enhancement algorithms. This paper summarizes the relevant evaluation methods for enhanced speech, including subjective audiometry, objective evaluation of speech quality and objective evaluation of speech intelligibility. According to the derivation process of Wiener filter, the gain function of Wiener filter is obtained. Then the Wiener filtering method based on prior SNR estimation is introduced in detail. The method is simple and the quality of enhanced speech is improved obviously. The experimental results of sentence and consonant corpus show that this method improves speech quality but does not improve the intelligibility of enhanced speech in real sense. This paper analyzes the reasons why speech intelligibility is not improved in enhanced speech, and studies the attenuation distortion and amplification distortion in enhanced speech amplitude spectrum from the perspective of residual SNR, and the intelligibility of enhanced speech will be seriously affected by the amplification distortion of amplitude spectrum larger than that of 6.02dB. The amplitude spectrum of the original pure speech is compared with the amplitude spectrum of the enhanced speech, and the distortion region of the amplitude spectrum is removed than that of the 6.02dB, and the intelligibility and quality of the enhanced speech are obviously improved compared with the noisy speech. It is impossible to have pure speech in real speech processing environment, which needs to be improved by prior signal-to-noise ratio (SNR). A prior signal-to-noise ratio (SNR) less than -10dB region is corrected and then the gain function of the filtering algorithm is modified. Then the amplitude spectrum is determined to be larger than the 6.02dB region and the region is constrained by the existing conditions. Finally, an improved Wiener filter enhancement algorithm with high intelligibility is obtained. The experimental results of sentence and consonant corpus show that the improved algorithm can improve the intelligibility of enhanced speech.
【學位授予單位】：太原理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN912.35

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

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本文編號：2207535