Aiming at multi-speaker communication scene in real life, an effective solution is designed and proposed based on researches of underdetermined blind speech separation method of target sound source's azimuth information and nonlinear time-frequency masking and BP speaker recognition technology, which can extract any target speaker's speech in any orientation. The solution is generally divided into two stages, one is target speech search and the other is target speech extraction. The search stage uses BP speaker recognition technology. The speech extraction stage uses the method of underdetermined blind speech separation based on sound source azimuth information by an improved potential function clustering and nonlinear time-frequency masking. The results show that the solution is feasible. It can effectively extract the target speaker's speech in any position from the mixed speech stream. The average SNRG is 8.68dB, the similarity coefficient is 85%, the recognition rate is 61%, and the running time is 20.6S.%于目标声源的方位信息与非线性时频掩蔽语音欠定盲分离方法和BP说话人识别技术的研究基础上,针对现实生活中多说话人交流场景,设计并提出了一种行之有效的解决方案,实现了对处于任意方位的任意目标说话人语音的提取.该方案总体上分目标语音搜索与提取两个阶段,搜索阶段采用了BP说话人识别技术,提取阶段采用了一种改进的势函数聚类声源方位信息与非线性时频掩蔽的语音欠定盲分离方法.实验结果表明:该方案具有可行性,可从混合语音流中有效提取处于任意方位的目标说话人语音,且效果较好,信噪比增益平均为8.68dB,相似系数为85%,识别率为61%,运行时间为20.6S.
展开▼
