现代电子技术2017，Vol.40Issue(22)：1-4,9,5.DOI:10.16652/j.issn.1004-373x.2017.22.001
基于语音增强方法的语音端点检测
Voice activity detection based on speech enhancement method
摘要
Abstract
The test results of voice activity detection(VAD)play a decisive role in the subsequent speech processing. To resolve the problem of low detection rate of speech endpoints at low signal-to-noise ratio(SNR),a method of combing speech en-hancement method based on deep belief network denoising with the traditional endpoint detection method is proposed. The deep belief network model is trained by large volumes of speech data to effectively map the nonlinear relationship between noisy speech and noise-free speech,and is made to become a good noise reduction filter. The effects of noisy speech and denoised speech on endpoint detection accuracy,and the correctness of endpoint detection at different SNRs are compared. The experi-mental results show that the method can improve the accuracy of VAD in the case of both stationary noise and non-stationary noise with low SNR.关键词
语音端点检测/深层置信网络/信噪比/语音处理Key words
voice activity detection/deep belief network/SNR/speech processing分类
信息技术与安全科学引用本文复制引用
包武杰,黄浩..基于语音增强方法的语音端点检测[J].现代电子技术,2017,40(22):1-4,9,5.基金项目
国家自然科学基金(61365005 （）
60965002) （）
