本文關鍵詞： 人工耳蝸 降噪算法 增益函數(shù) 顯式增益閾值　出處：《深圳大學》2017年碩士論文　論文類型：學位論文

【摘要】：人工耳蝸(Cochlear implant,CI)是目前能使重度感音性聽力障礙患者恢復聽覺感知的唯一裝置。它通過言語處理器對聲音信號提取包絡信息,經(jīng)非線性壓縮和振幅調(diào)制等處理,將聲音信號轉(zhuǎn)換為相應電極的電信號刺激殘留的聽覺神經(jīng),使患者恢復聽力。它在安靜環(huán)境下能為CI植入者提供較好的言語感知體驗,然而在噪聲環(huán)境下,大多數(shù)CI產(chǎn)品無法為植入者提供足夠的頻率分辨率、時域精細結構等信息,使CI植入者的言語識別率出現(xiàn)明顯的下降,嚴重影響他們在噪聲環(huán)境下的正常交流。因此,針對CI植入者在噪聲下言語感知差的問題開展降噪算法的研究具有重要意義。針對該問題,本文提出一種基于顯式增益閾值(apparent gain threshold,aGT)的參數(shù)維納濾波降噪算法。本文首先對人工耳蝸的背景知識、國內(nèi)外人工耳蝸降噪算法的發(fā)展和研究現(xiàn)狀進行敘述;其次重點介紹了Mauger提出的基于信噪比和參數(shù)維納增益函數(shù)的降噪算法,并針對該算法存在主要問題--需要經(jīng)過大量的測試實驗才能確定增益函數(shù)最優(yōu)參數(shù)---提出一種改進算法。通過實驗驗證分析aGT曲線與最優(yōu)參數(shù)(、)的關系,提出基于aGT的參數(shù)維納濾波降噪算法,將二維平面的最優(yōu)參數(shù)(、)尋找問題簡化為單個參數(shù)aGT的最優(yōu)化問題,從而極大地減少了測試者的參數(shù)調(diào)校實驗量。最后,本文通過聲碼器仿真聲實驗和CI植入者實驗驗證所提算法的降噪性能。由仿真聲實驗結果可知,大多數(shù)測試者在aGT為5dB時能獲得較好的言語識別率,不同通道數(shù)的選擇對于降噪算法的性能影響不大。與其他三種降噪方法的識別率比較發(fā)現(xiàn),當增益閾值為5dB時,本文提出的算法能達到與方法I和II相當?shù)慕翟胄Ч?而方法I和II中噪聲估計是在噪聲信號已知的情況下得到的。對比結果也表明基于感知特性的參數(shù)維納增益函數(shù)比二值掩蔽增益函數(shù)更適合CI植入者。從CI植入者的實驗結果可知,與正常聽力者相比,CI植入者更偏向于選擇大于0dB的增益閾值。同樣地,在aGT值為5dB時,大多數(shù)測試者可以得到較高的單詞識別率。
[Abstract]:Cochlear implant. At present, CI is the only device that can restore auditory perception in patients with severe sensorineural hearing impairment. It extracts envelope information from sound signal by speech processor and is processed by nonlinear compression and amplitude modulation. The sound signal can be converted into the corresponding electrode electrical signal to stimulate the residual auditory nerve, so that the patient can recover hearing. It can provide a better speech perception experience for CI implants in the quiet environment, but in the noise environment. Most CI products can not provide enough frequency resolution, time domain fine structure and other information for implants, so the speech recognition rate of CI implants decreased significantly. Therefore, it is of great significance to study the speech perception of CI implants under noise. In this paper, a parameter Wiener filter denoising algorithm based on explicit gain threshold gain threshold is proposed. Firstly, the background knowledge of cochlear implant is given. The development and research status of cochlear denoising algorithms at home and abroad are described. Secondly, the noise reduction algorithm based on signal-to-noise ratio and parameter Wiener gain function proposed by Mauger is introduced. Aiming at the main problem of the algorithm, which needs a lot of tests to determine the optimal parameter of the gain function, an improved algorithm is proposed. The aGT curve and the optimal parameter are analyzed by the experiment. A parameter Wiener filter denoising algorithm based on aGT is proposed, which simplifies the problem of finding the optimal parameters of two-dimensional plane to the optimization problem of single parameter aGT. In order to greatly reduce the parameters of the tester calibration experiment. Finally, the noise reduction performance of the proposed algorithm is verified by the vocoder simulation sound experiment and CI implant experiment. The result of the simulation acoustic experiment shows that the proposed algorithm can reduce the noise of the proposed algorithm. Most of the testers can obtain better speech recognition rate when aGT is 5 dB, and the choice of different channel numbers has little effect on the performance of the noise reduction algorithm. Compared with the other three noise reduction methods, it is found that the recognition rate of the proposed algorithm is better than that of the other three methods. When the gain threshold is 5 dB, the proposed algorithm can achieve the same denoising effect as that of methods I and II. In methods I and II, the noise estimation is obtained when the noise signal is known. The comparative results also show that the parameter Wiener gain function based on perceptual characteristics is more suitable for CI implants than the binary masking gain function. The experimental results of I implants showed that. Compared with the normal hearing group, CI implants were more inclined to choose a gain threshold greater than 0 dB. Similarly, when the aGT value was 5 dB, most of the subjects could get a higher word recognition rate.
【學位授予單位】：深圳大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN912.3;TN713

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