本文關(guān)鍵詞： 回聲消除 小波分析 雙端通話檢測(cè) 短時(shí)平均能量 基音周期 自適應(yīng)濾波算法 混合共軛梯度算法　出處：《江西理工大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著時(shí)代的進(jìn)步,科技的發(fā)展為各大通信設(shè)備商帶來(lái)機(jī)遇的同時(shí)也帶來(lái)了挑戰(zhàn)。隨著通信設(shè)備種類的增多,用戶對(duì)設(shè)備中語(yǔ)音質(zhì)量要求也越來(lái)越高。一個(gè)通信設(shè)備能夠擁有清晰的聲音也是作為語(yǔ)音通信產(chǎn)品最基本的條件,然而由于人們的生活環(huán)境的復(fù)雜化,在通話過(guò)程中,大多數(shù)的語(yǔ)音信號(hào)都會(huì)受到不同程度不同類型的回聲信號(hào)的干擾,影響語(yǔ)音通話的質(zhì)量,如何有效進(jìn)行通信設(shè)備的回聲消除就顯得尤為重要。文章通過(guò)對(duì)常見(jiàn)聲學(xué)回聲消除方法的研究,分別對(duì)自適應(yīng)回聲消除系統(tǒng)中的兩個(gè)主要模塊:自適應(yīng)回聲消除模塊與雙端檢測(cè)模塊,分別做了研究與改進(jìn)。(1)雙端通話檢測(cè)算法的研究:首先列舉了常見(jiàn)的雙端通話檢測(cè)算法,針對(duì)所列舉算法的不足,本文在傳統(tǒng)的雙端通話檢測(cè)算法的基礎(chǔ)上提出了一種改進(jìn)的小波域多特征值雙端通話檢測(cè)算法。改進(jìn)算法將自適應(yīng)濾波器的輸入信號(hào)與參考信號(hào)進(jìn)行小波分解,對(duì)分解后的小波子帶信號(hào)進(jìn)行小波閾值去噪處理,再對(duì)去噪后的低頻小波子帶進(jìn)行雙閾值能量判斷,判斷出語(yǔ)音信號(hào)所處的不同狀態(tài):靜音態(tài),活躍態(tài)與通話態(tài)。當(dāng)判定為靜音態(tài)與通話態(tài)時(shí),自適應(yīng)濾波器根據(jù)其判定的狀態(tài)做出相應(yīng)的處理;而活躍態(tài)的語(yǔ)音信號(hào)由于能量的增加較少,無(wú)法一次性判定出其所處的狀態(tài),需要對(duì)活躍態(tài)語(yǔ)音信號(hào)的基因周期進(jìn)行比較,進(jìn)而判斷出活躍態(tài)的通話狀態(tài),以便自適應(yīng)濾波器做出相應(yīng)的處理。(2)針對(duì)自適應(yīng)回聲消除算法:本文首先列舉了常見(jiàn)的自適應(yīng)濾波算法,針對(duì)所列舉算法的不足,提出了一種改進(jìn)的自適應(yīng)混合共軛梯度迭代算法,該算法將均值算法與混合共軛梯度迭代算法相結(jié)合,并應(yīng)用到自適應(yīng)濾波器的權(quán)值更新中。最后對(duì)提出的改進(jìn)的小波域多特征值雙端檢測(cè)算法與改進(jìn)的自適應(yīng)混合共軛梯度迭代算法分別進(jìn)行實(shí)驗(yàn)仿真。實(shí)驗(yàn)結(jié)果表明,改進(jìn)后的算法表現(xiàn)良好,且與理論相符。
[Abstract]:With the progress of the times, the development of science and technology brings opportunities as well as challenges for the major communication equipment manufacturers. It is also the most basic condition for a communication device to have a clear voice. However, due to the complexity of people's living environment, in the process of communication, Most of the speech signals will be disturbed by different types of echo signals, which will affect the quality of voice calls. How to effectively carry out echo cancellation of communication equipment is particularly important. Two main modules of adaptive echo cancellation system: adaptive echo cancellation module and two-terminal detection module are studied, and the algorithms of two-terminal call detection are studied and improved respectively: firstly, the common two-terminal call detection algorithms are listed. In view of the shortcomings of the listed algorithms, Based on the traditional two-terminal call detection algorithm, an improved multi-eigenvalue two-terminal call detection algorithm in wavelet domain is proposed, which decomposes the input signal and reference signal of adaptive filter by wavelet transform. The decomposed wavelet sub-band signal is de-noised by wavelet threshold, and the low-frequency wavelet sub-band after de-noising is judged by double threshold energy, and the different states of speech signal are determined: silent state. When the active state and the call state are determined, the adaptive filter makes corresponding processing according to the state determined by the active state, and the active state speech signal can not be determined in one time because of the small increase in energy. We need to compare the gene cycle of active speech signal, and then judge the active state of speech. So that the adaptive filter to do the corresponding processing. 2) for adaptive echo cancellation algorithm: firstly, this paper lists the common adaptive filtering algorithm, aiming at the shortcomings of the listed algorithm, An improved adaptive hybrid conjugate gradient iterative algorithm is proposed, which combines the mean algorithm with the hybrid conjugate gradient iterative algorithm. Finally, the improved multi-eigenvalue two-terminal detection algorithm in wavelet domain and the improved adaptive hybrid conjugate gradient iterative algorithm are simulated, respectively. The experimental results show that, The improved algorithm performs well and agrees with the theory.
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN912.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 魏臻;凌勇;程磊;程運(yùn)安;;IP語(yǔ)音通話中回聲消除算法的研究[J];合肥工業(yè)大學(xué)學(xué)報(bào)(自然科學(xué)版);2011年05期

2 肖繼學(xué);陳光，

本文編號(hào)：1545463