An SAD Algorithm based on SGMM and Phoneme Combination

	An SAD Algorithm based on SGMM and Phoneme Combination
	Chen, Xiao; Xu, Bo
	2015-12
会议名称	International Conference on Computer Science and Network Technology
会议录名称	Proceedings of the Fourth International Conference on Computer Science and Network Technology
会议日期	19-20
会议地点	Harbin
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.
关键词	Speech Activity Detection Subspace Gaussian Mixture Model Phoneme Combination
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/41130
专题	复杂系统认知与决策实验室_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],2015.