用递归滤波器对高斯噪声和真实噪声干扰下增强噪声压缩语音信号的性能分析

M. Suman, H. Khan, M. Latha, D. Kumari
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引用次数: 0

摘要

语音增强是指使用信号处理技术提高退化语音信号的可理解性和/或质量。由于语音信号中的噪声含量随时间和应用的不同而改变其性质和特征,语音增强一直是一个非常困难的问题。使用语音增强技术不能同时保持语音信号的质量和可理解性。所以一般来说,这两者之间保持着一种权衡。在语音通信中,有许多应用需要语音增强,例如:VoIP,免提通信,助听器,应答机,语音识别,电话会议系统,汽车和移动电话。在这项工作中,主要关注的是语音增强算法的发展,该算法在语音信号的质量和可理解性之间保持适当的权衡。这可以利用语音信号中的时间和频谱信息来实现。本工作还重点研究了语音信号压缩版的增强问题,以提高语音信号的可理解性。诸如信噪比(SNR)、平均意见分数(MOS)、基音和共振峰等性能指标用于发现语音增强算法的性能,这些性能指标因应用而异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance analysis of enhanced noisy compressed speech signal corrupted by Gaussian and real world noise using recursive filter
Speech Enhancement refers to the improvement in the intelligibility and or the quality of the degraded speech signal using signal processing techniques. Till recent days speech enhancement is a very difficult problem because the noise content in the speech signals varies its nature and characteristics with time and application to application. Using speech enhancement techniques the quality and intelligibility of a speech signal can't be preserved simultaneously. So generally a trade off is maintained between these two. In speech communication there are number of applications where speech enhancement is required for Example: VoIP, hands free communication, hearing aids, answering machines, speech recognition, teleconferencing systems, car and mobile phones. In this work the main focus is on the development of speech enhancement algorithm that maintains a proper tradeoff between quality and intelligibility in the speech signal. This can be made possible using the time and spectral information in the speech signal. This work also focus on the problem of enhancing the compressed version of the speech signal, to improve the intelligibility of the speech signal. The performance measures like Signal to Noise Ratio (SNR), Mean opinion Score (MOS), Pitch and Formants used to find the performance of a speech enhancement algorithm which varies from application to application.
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