自适应语音消噪算法的研究与应用

针对语音通信中的消噪算法进行了研究。经研究发现，消噪算法在收敛速度与稳态误差之间始终存在着矛盾。为改善语音中的消噪能力，减少误差，在G SVSLMS算法的基础上，提出了一种改进的噪声消除算法，即利用引入一个关于误差的反正切函数来改进步长因子，并通过计算机仿真证实了改进算法具有良好的收敛性能和稳态性能，最后利用传统的LMS算法、G SVSLMS算法和改进算法对带有噪声的信号进行了消噪处理，结果表明：在三种算法中，改进算法的噪声消除效果最好。

Research and application of adaptive speech denoising algorithms

According to the noise problem of voice communication, the denoising algorithm is studied. The study finds that the algorithm always has a contradiction between the convergence speed and the steady-state error. In order to improve the denoising capacity in the voice and decrease error, a new algorithm is proposed based on the G-SVSLMS algorithm. It uses the error arctangent function to change the step-size factor. And computer simulation demonstrates that the algorithm has the good convergence and steady-state performance. Finally, signals with noise are denoised by the traditional LMS algorithm, the traditional G-SVSLMS algorithm and the improved algorithm. The results show that the improved algorithm has the best noise cancellation effect amongst the three algorithms.