An SAD Algorithm based on SGMM and Phoneme Combination

	An SAD Algorithm based on SGMM and Phoneme Combination
	Chen, Xiao; Xu, Bo
	2015-12
会议日期	19-20
会议地点	Harbin
关键词	Speech Activity Detection Subspace Gaussian Mixture Model Phoneme Combination
英文摘要	Speech activity detection (SAD) is the key preprocess of speech application. This paper proposed a subspace Gaussian mixture model (SGMM) and phoneme combination based SAD algorithm. This algorithm is efficient, small and can utilize speech recognition corpus directly. Results indicate that, compared with the baseline, our proposed method results in an absolute improvement of 4.9% frame error rate and 10% average hit rate, respectively. Our approach finally achieves a frame error rate of 5.1% and an average hit rate of 91.5%. The model size is just 809.5K.
会议录	Proceedings of the Fourth International Conference on Computer Science and Network Technology
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/41130]
专题	数字内容技术与服务研究中心_听觉模型与认知计算
通讯作者	Chen, Xiao
推荐引用方式 GB/T 7714	Chen, Xiao,Xu, Bo. An SAD Algorithm based on SGMM and Phoneme Combination[C]. 见:. Harbin. 19-20.