车载环境下语音增强的研究

RESEARCH ON SPEECH ENHANCEMENT ALGORITHM UNDER ON-BOARD ENVIRONMENT

针对车载环境下语音系统受到外界强噪声的干扰而导致识别精度降低以及通信质量受损的问题,提出一种自适应MMSE-LSA估计与TEO(Teager Energy Operator)能量端点检测相结合的语音增强算法。TEO端点检测可以将语音分为语音段和非语音段,从而在噪声估计时可以更好地跟踪噪声的变化,得到更加准确的先后验信噪比,使增强后的语音最大限度地接近纯净语音,而且对车载噪声的增强效果比其他噪声更好。在车载环境中进行实验,结果显示该方法与MMSE-LSA以及传统的谱减法相比,提高了输出信噪比,减弱了音乐噪声,在可懂度和清晰度方面均具有优势。

Voice system could be disturbed by external strong noise under on-board environment, which will lead to decline in accuracy of recognition and damage of communication quality. In order to solve this problem, we proposed a speech enhancement algorithm combining adaptive MMSE-LSA estimation and TEO （Teager energy operator） endpoint detectiQn. According to TEO endpoint detection method, speech can be divided into voice segment and non-voice segment so that in noise estimation the changes of noise can be better tracked and more accurate priori sNR and posterior SNR can be gained as well, this makes the enhanced speech sufficiently approach the original speech. In addition, ＂lEO endpoint detection has a much better effect in enhancing vehicle noise than any other noises. Experiment was carried out under on-board environment, results showed that this method, compared with MMSE-LSA estimation and traditional spectral subtraction, improved the output SNR, reduced the music noise, and had the advantages in both intelligibility and clarity.