本文選題：語(yǔ)音增強(qiáng) + 小波閾值��； 參考：《深圳大學(xué)》2017年碩士論文

【摘要】：隨著計(jì)算機(jī)與數(shù)字信號(hào)處理技術(shù)的不斷發(fā)展,語(yǔ)音信號(hào)處理技術(shù)也不斷完善與成熟,并以視頻會(huì)議、手機(jī)、網(wǎng)絡(luò)視訊等各種形式廣泛應(yīng)用于現(xiàn)實(shí)生活里面。但是各種各樣的噪聲會(huì)干擾語(yǔ)音通訊設(shè)備的通訊效果,嚴(yán)重妨礙了人們正常的交流與工作。所以,怎樣有效降低噪聲帶來(lái)的問(wèn)題,提高有用語(yǔ)音信號(hào)質(zhì)量,引起了海內(nèi)外許多專家研究者們的興趣。目前也出現(xiàn)了較多的語(yǔ)音增強(qiáng)算法,一些在輸入噪聲較低情況下增強(qiáng)效果較好,高噪聲強(qiáng)度輸入下,增強(qiáng)效果不理想。因此,本文在針對(duì)各種信噪比輸入條件下進(jìn)行研究。主要做了如下工作或改進(jìn):1:分析了小波去噪理論知識(shí),主要深入研究小波閾值函數(shù)降噪算法,其目的是保留帶噪語(yǔ)音信號(hào)中有用語(yǔ)音小波系數(shù),抑制噪聲系數(shù)。對(duì)一些小波閾值函數(shù)存在不連續(xù)、不同分解層數(shù)閾值恒定以及會(huì)產(chǎn)生恒定誤差等缺點(diǎn)。提出改進(jìn)的帶調(diào)整參數(shù)連續(xù)小波閾值函數(shù),并采用粒子群尋優(yōu)法尋找改進(jìn)閾值函數(shù)在背景噪聲中的最優(yōu)值,最后將改進(jìn)的函數(shù)與貝葉斯閾值方法相結(jié)合,進(jìn)行小波重構(gòu)處理后,得到處理后的語(yǔ)音信號(hào)系數(shù)。將提出的閾值函數(shù)與其他已存閾值函數(shù)去噪效果對(duì)比,仿真實(shí)驗(yàn)結(jié)果表明在語(yǔ)音輸出信噪比、降低有用信號(hào)失真及抑制背景噪聲等方面有一定提高。2:改進(jìn)型閾值函數(shù)的小波去噪算法在輸入噪聲強(qiáng)度不高的情況下降噪效果明顯,但是在低信噪比下還是殘留一些雜聲,因此,為進(jìn)一步提高增強(qiáng)語(yǔ)音去噪算法效果,將帶噪語(yǔ)音信號(hào)經(jīng)過(guò)改進(jìn)型閾值函數(shù)小波去噪后作為先驗(yàn)信息,再結(jié)合卡爾曼濾波算法,得到最終的增強(qiáng)信號(hào)。利用MATLAB平臺(tái)進(jìn)行實(shí)驗(yàn),其結(jié)果表明該結(jié)合法能在高噪聲輸入條件下取得更好的增強(qiáng)效果。3:語(yǔ)音信號(hào)采集與顯示界面的編寫(xiě),在PC Windows操作系統(tǒng)上,采用VC++6.0軟件編寫(xiě)的MFC界面,通過(guò)對(duì)USB聲卡和Windows所提供的音頻Wave類(lèi)中函數(shù)完成對(duì)聲卡中音頻編程,實(shí)現(xiàn)語(yǔ)音采集界面。調(diào)用Windows所給的繪圖API函數(shù),實(shí)現(xiàn)波形數(shù)據(jù)顯示功能。
[Abstract]:With the development of computer and digital signal processing technology, voice signal processing technology has been improved and matured, and has been widely used in real life in various forms such as video conference, mobile phone, network video. However, all kinds of noise will interfere with the communication effect of voice communication equipment, which seriously hinders people's normal communication and work. Therefore, how to effectively reduce the problems caused by noise and improve the quality of useful speech signal has attracted the interest of many experts and researchers at home and abroad. At present, there are many speech enhancement algorithms, some of which have better enhancement effect when the input noise is low, but the enhancement effect is not ideal under the high noise intensity input. Therefore, this paper studies on various SNR input conditions. The main work of this paper is as follows: firstly, the wavelet denoising theory is analyzed, and the wavelet threshold function denoising algorithm is studied in depth. The purpose of the algorithm is to retain the useful speech wavelet coefficients and suppress the noise coefficients in noisy speech signals. For some wavelet threshold functions there are some disadvantages such as discontinuity constant threshold of different decomposition layers and constant error. An improved continuous wavelet threshold function with adjusted parameters is proposed, and the particle swarm optimization method is used to find the optimal value of the improved threshold function in background noise. Finally, the improved function is combined with Bayesian threshold method to reconstruct the wavelet. The speech signal coefficients after processing are obtained. The proposed threshold function is compared with that of other existing threshold functions. The simulation results show that the signal-to-noise ratio (SNR) of the speech output is obtained. In some aspects, such as reducing useful signal distortion and suppressing background noise, the wavelet denoising algorithm with improved threshold function can reduce noise obviously when the input noise intensity is not high, but it still has some residual noise under low SNR. Therefore, in order to further improve the effect of enhanced speech denoising algorithm, the noisy speech signal is de-noised by the improved threshold function wavelet as the prior information, and then the final enhanced signal is obtained by combining the Kalman filter algorithm. The results show that the combined method can achieve better enhancement effect under the condition of high noise input. The interface of voice signal acquisition and display is compiled. On PC Windows operating system, MFC interface is written with VC 6.0 software. Through the function of USB sound card and the audio wave class provided by Windows, the audio program of the sound card is completed, and the interface of voice acquisition is realized. The drawing API function given by Windows is called to realize the display function of waveform data.
【學(xué)位授予單位】：深圳大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TN912.35

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