本文選題：混響　切入點(diǎn)：麥克風(fēng)陣列　出處：《南京信息工程大學(xué)》2017年碩士論文

【摘要】：麥克風(fēng)陣列信號(hào)處理在助聽(tīng)設(shè)備、車載免提通訊系統(tǒng)、遠(yuǎn)程視頻會(huì)議環(huán)境以及機(jī)器人聽(tīng)覺(jué)等語(yǔ)音信號(hào)處理中有著普遍的應(yīng)用。但目前存在許多問(wèn)題在麥克風(fēng)陣列信號(hào)處理方面:首先,眾所周知麥克風(fēng)陣列接收到的語(yǔ)音是寬帶信號(hào),如果用傳統(tǒng)的窄帶波束形成方法來(lái)處理,會(huì)造成波束形成阻帶發(fā)生畸變,無(wú)法抑制干擾信號(hào);其次,通常存在麥克風(fēng)通道的增益差異、相位偏移和位置抖動(dòng)等不確定性造成的失配誤差,而這些誤差也會(huì)造成麥克風(fēng)陣列信號(hào)處理的性能下降;最后,在相對(duì)封閉的幾何空間內(nèi)麥克風(fēng)陣列與語(yǔ)音信號(hào)播放的位置存在一定距離時(shí),麥克風(fēng)陣列接收的信號(hào)不單僅是語(yǔ)音的直達(dá)信號(hào),同時(shí)還有語(yǔ)音源在墻壁上多次反射的信號(hào),從而導(dǎo)致語(yǔ)音的清晰度下降。為此,本文分析研究了混響環(huán)境下穩(wěn)健麥克風(fēng)陣列波束形成語(yǔ)音增強(qiáng)算法,并通過(guò)理論分析及計(jì)算機(jī)仿真和實(shí)驗(yàn)實(shí)測(cè)驗(yàn)證所提算法的有效性。主要工作如下:1.針對(duì)寬帶信號(hào)波束形成器存在畸變的問(wèn)題,給出了基于離散空間響應(yīng)偏差函數(shù)的自適應(yīng)加權(quán)寬帶頻率不變波束形成算法。該算法基于線性約束最小方差準(zhǔn)則,首先通過(guò)離散空間響應(yīng)偏差函數(shù)的二項(xiàng)式計(jì)算界定陣列空間響應(yīng)偏差函數(shù)的均衡矩陣;其次將該均衡矩陣以系數(shù)加權(quán)的形式寫(xiě)入到該準(zhǔn)則的波束形成算法目標(biāo)優(yōu)化函數(shù)中進(jìn)行權(quán)值計(jì)算;最后再將系數(shù)加權(quán)頻率不變波束形成算法中的加權(quán)系數(shù)定義為場(chǎng)點(diǎn)距離和信號(hào)頻率的函數(shù),該加權(quán)函數(shù)具有動(dòng)態(tài)特性并采用自適應(yīng)原理進(jìn)行更新。通過(guò)仿真實(shí)驗(yàn)表明,該算法波束頻率不變性能較好,阻帶水平整體較低,在設(shè)置的干擾方向上形成了較深的零陷。2.針對(duì)現(xiàn)實(shí)環(huán)境中的麥克風(fēng)通道特征誤差導(dǎo)致寬帶波束形成器性能下降的問(wèn)題,給出了基于線性約束最小方差對(duì)角加載的穩(wěn)健頻率不變波束形成算法。該算法首先在線性約束最小方差準(zhǔn)則的目標(biāo)函數(shù)基礎(chǔ)上以系數(shù)加權(quán)的形式結(jié)合離散空間響應(yīng)偏差二項(xiàng)式矩陣,實(shí)現(xiàn)頻率不變波束形成器;然后采用白噪聲增益作為約束條件寫(xiě)入線性約束最小方差目標(biāo)函數(shù)優(yōu)化的準(zhǔn)則中,分析白噪聲增益約束值大小,以提高麥克風(fēng)特征誤差的穩(wěn)健性,主要解決問(wèn)題是麥克風(fēng)的增益偏差、相位偏移和位置抖動(dòng)等因素的不確定性造成低頻信號(hào)全通濾波,從而導(dǎo)致波束形成器性能下降;最后通過(guò)拉格朗日乘子法計(jì)算固定權(quán)值和凸優(yōu)化工具箱迭代求解得到最優(yōu)權(quán)矢量。通過(guò)仿真實(shí)驗(yàn)表明,該算法波束穩(wěn)健性能較好,穩(wěn)健后的波束形成器的低頻性能得到改善,陣列增益高、方向性較好。3.針對(duì)封閉環(huán)境中往往受到混響效應(yīng)影響導(dǎo)致語(yǔ)音信號(hào)清晰度下降的情況,給出了基于混響環(huán)境下線性約束最小方差分頻的改進(jìn)維納濾波后置波束形成算法。該算法基于延遲加權(quán)求和波束形成的維納后置濾波結(jié)構(gòu)上進(jìn)行改進(jìn)采用線性約束最小方差波束形成準(zhǔn)則.改進(jìn)的算法首先假設(shè)每個(gè)頻段上混響時(shí)間不同的特性,在麥克風(fēng)陣列接收信號(hào)的進(jìn)行分頻處理,將波束形成算法應(yīng)用到高低頻域的子帶中,提高了混響抑制的精度;其次麥克風(fēng)陣列接收到混響信號(hào)的直達(dá)波和反射波之間是不相關(guān)的,利用麥克風(fēng)陣列接收信號(hào)的空間信息解決維納濾波器的估計(jì)問(wèn)題。通過(guò)仿真測(cè)驗(yàn)結(jié)果表明,該算法對(duì)混響抑制具有明顯的改善,且提高了語(yǔ)音增強(qiáng)系統(tǒng)的評(píng)價(jià)指標(biāo)得分。4.針對(duì)麥克風(fēng)通道物理特性失配誤差和封閉空間中引起的混響對(duì)語(yǔ)音清晰度的影響,研究了音頻信號(hào)采集實(shí)驗(yàn)和數(shù)據(jù)分析。首先,在消聲室中搭建實(shí)驗(yàn)平臺(tái),固定聲源采集麥克風(fēng)陣列數(shù)據(jù),對(duì)采集的數(shù)據(jù)用本文提出的穩(wěn)健算法進(jìn)行驗(yàn)證;其次,在混響較強(qiáng)車庫(kù)環(huán)境中搭建實(shí)驗(yàn)平臺(tái),固定聲源采集混響陣列數(shù)據(jù),對(duì)采集的數(shù)據(jù)進(jìn)行本文提出的混響抑制算法驗(yàn)證。通過(guò)消聲室和車庫(kù)實(shí)際環(huán)境實(shí)測(cè)的算法輸出信號(hào)的語(yǔ)譜圖實(shí)驗(yàn)結(jié)果可以看出,所提出的算法與仿真結(jié)果預(yù)期一致。
[Abstract]:Microphone array signal processing in hearing aid equipment, hands-free communication system, has the widespread application of remote video conferencing environment and robot auditory processing of speech signal. But there are many problems in the microphone array signal processing: first of all, as everyone knows the received speech Mike wind array is a wideband signal, if using the traditional narrow-band beamforming the method to deal with, will cause the beamforming stopband distortion, can suppress the interference signal; secondly, there is the microphone gain difference channel, caused by phase shift and position jitter uncertainty such as mismatch errors, these errors will degrade the performance of microphone array signal processing; finally, playing with the microphone array speech signal in the geometric space is relatively closed position within a certain distance from the microphone array, signal receiving not only voice The direct signal, signal and speech source reflected many times on the wall, which leads to the speech articulation. Therefore, this paper studies the reverberation robust beamforming microphone array speech enhancement algorithm is effective, and through theoretical analysis and computer simulation and experimental verification of the proposed algorithm. The main work is as follows: 1. for wideband signal beamforming distortion problem, given the discrete spatial response adaptive weighted wideband frequency deviation function invariant beamforming algorithm. The algorithm based on linear constrained minimum variance criterion based on the first through the discrete space response function calculation deviation binomial response equilibrium matrix definition array spatial deviation function; secondly the equilibrium matrix the weighted coefficient of form written to the criteria of the beam forming algorithm to optimize the weights of target calculation function; Finally, the weighted coefficient of frequency invariant beamforming algorithm in the weighted coefficient is defined as a function of field distance and signal frequency, the weighting function is dynamic and updated by adaptive principle. The simulation results show that the algorithm performance is frequency invariant, the stopband level is low, in the direction of interference on the setting the formation of deep nulls for.2. microphone channels characteristic error in real environment leads to broadband beamformer performance degradation problem, presents a robust frequency linear constrained minimum variance diagonal loading beamforming algorithm based on invariant. Firstly, the objective function based on linear constrained minimum variance on the weighted coefficient of combination the discrete space response bias binomial matrix, to achieve frequency invariant beamformer; then the white noise gain as the constraint condition of writing The linear constrained minimum variance objective function optimization criterion, value analysis of white noise constraint, in order to improve the error robustness of microphone characteristics, mainly solves the problems of deviation of the microphone gain, phase shift and position jitter and other factors of uncertainty caused by the low frequency signal of all pass filter, which leads to the performance of the beamformer decreased; finally by Lagrange multiplier method to calculate the fixed weights and iterative convex optimization toolbox to obtain the optimal weight vector. The simulation results show that the algorithm robust performance, low frequency performance robust beamformer has the improved array, high gain, good direction for.3. closed environment is often caused by the reverberation effect of speech signal loss of clarity the improved Wiener filter, rear beam reverberation frequency based on linear constrained minimum variance is given The formation algorithm based on Wiener post filtering structure delay weighted sum beamforming was improved by linear constrained minimum variance beamforming criterion. The algorithm begins with the assumption that the characteristics of each band in different reverberation time, microphone array receiving signal frequency processing, beamforming algorithm is applied to the low frequency subband in improving the accuracy of reverberation suppression; second microphone array receives the reverberation signal between the direct wave and reflected wave is not related to the spatial information of a received signal using a microphone array to solve the estimation problem of the Wiener filter. The simulation test results show that this algorithm has obvious improvement of reverberation suppression and improve the.4. evaluation. The index score system according to physical characteristics of microphone channel mismatch and reverberation caused by the enclosed space of speech enhancement The clarity of the influence, on the audio signal analysis and data acquisition experiment. First, build in anechoic chamber experimental platform, fixed sound source collecting microphone array data to validate the robust algorithm, the data collected in this paper; secondly, to build a strong reverberation environment in the garage experiment platform, fixed source acquisition reverberation array the data on the data collected in this paper the reverberation suppression algorithm verification. Through the algorithm output signal of anechoic room and garage actual environment according to the measured spectrum experiment results show that the proposed algorithm and the simulation results as expected.

【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN912.3

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