基于计算听觉场景分析的混合语音信号分离算法研究  

Research on speech separation based on computational auditory scene analysis

作　　者：屈俊玲[1] 李鸿燕[1] 

机构地区：[1]太原理工大学信息工程学院,太原030024

出　　处：《计算机应用研究》2014年第12期3822-3824,共3页Application Research of Computers

基　　金：山西省自然科学基金资助项目(2013011016-1);国家教育部博士点基金资助项目(2011081047)

摘　　要：人耳听觉系统能够在强噪声的环境下区分出自己感兴趣的语音,基于计算听觉场景分析(CASA)的基本原理,其重点和难点是找到合适的声音分离线索,完成目标语音信号和噪声信号的分离。针对单通道浊语音分离的问题,提出了一种以基音为线索的浊语音信号分离算法。在白噪声、鸡尾酒会噪声等六种噪声干扰条件下,通过仿真实验结果表明,相比于传统的谱减法,语音分离算法的输出信噪比平均提高了7.47 d B,并有效抑制了干扰噪声,改善了分离效果。The human auditory system shows a remarkable capacity for speech segregation. Based on the principle of computational auditory scene analysis（ CASA）,the vital task was to find the right auditory cues to separate target voice. For monaural speech segregation,this paper proposed voiced speech separation algorithm based on pitch clues. Under the condition of six different noises,such as white noise,cocktail party noise,the experimental results show that the average target speech SNR is improved by 7. 47 d B compared with the traditional spectral subtraction,this proposed algorithm also effectively restrained the noise and improved the performance of voiced separation.

关 键 词：语音分离 计算听觉场景分析 基音 分段 听觉流 

分 类 号：TN912.3[电子电信—通信与信息系统] TP301.6[电子电信—信息与通信工程]