本文選題：語音增強(qiáng)　切入點(diǎn)：變換域　出處：《煙臺大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：現(xiàn)實(shí)生活和工作中,人們的學(xué)習(xí)、工作及娛樂活動多以語音的傳輸為橋梁,但語音在傳輸過程中不可避免地會受到外界噪聲的干擾,從而導(dǎo)致最終接收到的語音信號質(zhì)量與可懂度下降,嚴(yán)重影響人們的工作和生活品質(zhì)。而要使接收到的語音信號質(zhì)量和可懂度得到提高、更符合人耳的主觀感受,就必須對被污染的語音進(jìn)行去噪處理。語音增強(qiáng)即是對帶噪語音信號進(jìn)行處理,以盡可能地消除背景噪聲、恢復(fù)出原始語音信號的過程。目前,按照語音信號處理方式的不同可以將語音增強(qiáng)算法分為兩大類,即時域語音增強(qiáng)算法和變換域語音增強(qiáng)算法。由于變換域中語音和噪聲能量更集中、兩者之間的特征信息相對時域更便于處理,故在變換域中實(shí)現(xiàn)語音增強(qiáng)的算法已成為目前國內(nèi)外學(xué)者研究的重點(diǎn)。本文研究工作主要在離散余弦變換(DCT,Discrete Cosine Transform)域內(nèi)圍繞基于維納濾波的語音增強(qiáng)技術(shù)展開,通過分析和研究現(xiàn)有語音增強(qiáng)算法中增益因子的不足和缺陷,基于語音信號的統(tǒng)計模型,采用雙態(tài)維納濾波技術(shù)對其進(jìn)行改進(jìn),提出了新型的語音增強(qiáng)算法,并從理論和實(shí)驗(yàn)仿真兩個方面驗(yàn)證了提出算法的性能。本文的主要研究和創(chuàng)新工作具體如下:首先,對現(xiàn)有變換域中語音增強(qiáng)算法中增益因子的取值問題進(jìn)行了研究,利用實(shí)際的語音及噪聲數(shù)據(jù)重點(diǎn)分析了DCT域中純凈語音系數(shù)和噪聲系數(shù)之間的符號關(guān)系,發(fā)現(xiàn)了傳統(tǒng)維納濾波語音增強(qiáng)技術(shù)中存在的不足;其次,基于前文的實(shí)驗(yàn)分析結(jié)果,采用雙態(tài)維納濾波對原有算法進(jìn)行了有效改進(jìn),同時結(jié)合DCT域中常用的高斯及拉普拉斯模型分別對語音和噪聲信號進(jìn)行建模,設(shè)計出了三種統(tǒng)計模型下的雙態(tài)維納濾波語音增強(qiáng)算法;最后,通過理論分析和仿真實(shí)驗(yàn)驗(yàn)證了本文研究算法的有效性和優(yōu)越性,同時對全文進(jìn)行了總結(jié),并對所研究語音增強(qiáng)技術(shù)的未來發(fā)展?fàn)顩r做出了展望。
[Abstract]:In real life and work, people's study, work and entertainment mostly take the voice transmission as the bridge, but in the transmission process, the voice will inevitably be interfered by the external noise. As a result, the final received speech signal quality and intelligibility decline, seriously affecting the quality of people's work and life. To improve the quality and intelligibility of the received speech signal, it is more in line with the subjective feelings of the human ear. Speech enhancement is the process of processing noisy speech signal in order to eliminate background noise as much as possible and recover the original speech signal. According to different speech signal processing methods, speech enhancement algorithms can be divided into two categories, instant speech enhancement algorithm and transform domain speech enhancement algorithm. The characteristic information between the two is easier to process than time domain. Therefore, the implementation of speech enhancement in transform domain has become the focus of scholars at home and abroad. The research work in this paper is mainly focused on Wiener filter based speech enhancement technology in discrete cosine transform (DCT / discrete Cosine transform) domain. By analyzing and studying the deficiency and defect of gain factor in existing speech enhancement algorithms, based on the statistical model of speech signal, a novel speech enhancement algorithm is proposed, which is improved by using two-state Wiener filter technology. The performance of the proposed algorithm is verified by theoretical and experimental simulation. The main research and innovation work of this paper is as follows: firstly, the gain factor in the existing speech enhancement algorithm in transform domain is studied. The symbolic relationship between pure speech coefficients and noise coefficients in DCT domain is analyzed by using actual speech and noise data, and the shortcomings of traditional Wiener filter speech enhancement techniques are found. The two-state Wiener filter is used to improve the original algorithm effectively. At the same time, combined with Gao Si and Laplace models in DCT domain, the speech and noise signals are modeled, respectively. This paper designs three kinds of two-state Wiener filter speech enhancement algorithm under three statistical models. Finally, through theoretical analysis and simulation experiments, the validity and superiority of this algorithm are verified, and the full text is summarized. The future development of the speech enhancement technology is prospected.
【學(xué)位授予單位】：煙臺大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN912.35

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