计算机工程与应用Issue(16)：196-200,5.DOI:10.3778/j.issn.1002-8331.1204-0358
语音分离与HMM相结合的语音增强方法
Speech enhancement approach based on speech separation using HMM
摘要
Abstract
There are two typical speech enhancement algorithms based on HMM(Hidden Markov Model)which are MAP (Maximum A Posteriori)estimator and MMSE(Minimum Mean-Square Error)estimator. Both algorithms have high computa-tional complexity, and the former can’t handle non-stationary noise. In response to these shortcomings, with the speech separa-tion technology as reference, speech enhancement algorithm based on speech separation using HMM is designed. This algorithm uses the multi-state AR-HMM which is applied to non-stationary noise condition to decode the mixed state sequence of noisy speech under the speech model and noise model. Then, the decoded speech is estimated by speech separation method using maxi-mization model theory which avoids iterative procedure and huge computation so that the complexity is reduced. The experi-ments also show that the proposed algorithm can effectively remove the stationary noise and non-stationary noise, improve the PESQ(Perceptual Evaluation of Speech Quality)score and the algorithm time is under control too.关键词
语音增强/语音分离/非平稳噪声/基于HMM的语音增强Key words
speech enhancement/speech separation/non-stationary noise/speech enhancement based on HMM分类
信息技术与安全科学引用本文复制引用
刘凤增,李国辉,唐敏..语音分离与HMM相结合的语音增强方法[J].计算机工程与应用,2013,(16):196-200,5.基金项目
国家自然科学基金（No.61170158）。 （）
