- 學位論文
模擬應用適應性濾波器於具雙麥克風之手機裝置的抗噪研究
On the Application of the Adaptive Filters to Reduce the Noise of the Mobile Phone Devices with Dual-Microphone
摘要
隨著手機科技的進步，其功能也越來越多樣化，但是對於通話的品質才是使用者最原始的要求。然而撥打手機的使用者所在環境中難免會存在著噪音，造成想要表達的訊息無法清楚讓接聽者接收。而本文即模擬手機裝置的雙麥克風所收集之訊號，應用適應性濾波器消除環境噪音，使得接聽者所聆聽到的訊息更加清楚及完整。 本文由中華民國計算語言學會所發行的國語語音資料庫選出四種語音訊號作發話者的聲音，再利用訊號在時域以及頻域的特徵，由端點偵測找尋能量與熵值藉此判斷音訊開始和結束的位置，進而作為訊號進入雙麥克風之前處理。而演算法的選擇上，本文提出以最小均方、正規化最小均方和小波最小均方法來做為調整濾波器之權向量的方法。為了測試適應性濾波器對於消除窄頻以及寬頻噪音的優劣性，本文以三種不同頻率的正弦訊號先行測試適應性濾波器對於窄頻噪音消除的效能，進而將此方法延伸於消除寬頻訊號中的高斯白噪音與高斯粉紅噪音。最小均方與正規化最小均方法是由雙麥克風收集訊號後，並對噪音做消除的動作，由於適應性濾波器對於窄頻噪音消除效能較佳，本文藉由小波最小均方法將訊號分別經過拆解、除噪和組合的過程，使得演算過程以平行架構的方式作運算，並利用軟體MatLab去模擬應用在實際硬體上的可能性。 模擬結果發現，適應性濾波器對於消除窄頻噪音以及寬頻噪音，其訊噪比的提升和降低相對誤差的能力皆有一定的效果，也充份保留原始訊號的語音特性，使得在消除噪音的同時，不至於讓原始的語音訊號失真。當訊號長度較長，則適應性濾波器能以多次數的迭代方式使得訊號擁有較好的收斂效果。
並列摘要
The cell phone technology is rapidly making its changes, adding more and more variety to its functions. But the most essential demand from the cell phone users is merely an excellent quality of communication. However, it is rare for most of us to converse over the phone without a hint of background noise or the likes, forcing us, as a result, to have misunderstandings or a void in our communication. In this thesis, we will attempt to utilize an adaptive algorithm to optimize the information collected from the dual-microphone. Four of the speech signals were selected from the MAT Speech Database, preserved by the Computational Linguistics and Chinese Language Processing Association, to serve as mock speeches for the speakers in this observation. Furthermore, a signal based on the features of the time domain and the frequency domain was utilized, along with the help of the end-point detector, to find out the amount of energy and entropy needed to determine the location of a signal's starting and ending point. Then through this, the signal was able to be determined before it is received. As for the employment of the adaptive algorithm, this thesis has cited a number of periodicals and theses to help readers gain a better understanding of the features of the active noise cancellation system. Moreover, this thesis adopted the least mean square algorithm, the normalized least mean square algorithm, and the wavelet based least mean square algorithm as expedients in eliminating background noises. Because our environment is filled with noises of various frequencies or energy, and in order to recognize the pros and cons of the different algorithms being used to eliminate the broadband and narrowband interferences, the sinusoidal signal with the frequencies at 200Hz, 1000Hz, and 2000Hz was implemented to test out how well and efficient the algorithms are able to eliminate the narrowband noises. This test will further attempt to exclude the Gaussian white noise and the Gaussian pink noise in the broadband. The two methods, the least mean square algorithm and the normalized least mean square algorithm, both directly eliminated noise after the dual-microphone had collected the signals. However, it was observed that the adaptive algorithm served to better eliminate the narrowband noises. Therefore, the Wavelet based least mean square algorithm was utilized to decompose, de-noise, and recompose the signals in attempt to parallelize the calculation process. The software, MatLab, was also employed to stimulate the possibilities when the algorithm is applied to the actual hardware. The result showed that the adaptive algorithm had great effects upon the elimination of both narrowband and broadband noises, and it efficiently preserved the completion of the original speech signals to minimize the distortion. When the signal was longer, the adaptive algorithm was observed to perform a greater convergence effect through number of iterations. Therefore, the algorithm had a greater performance on the function of de-noising.