Evaluation of the deep nonlinear metric learning based speaker identification  on the large scale of voiceprint corpus

	Evaluation of the deep nonlinear metric learning based speaker identification on the large scale of voiceprint corpus
	Feng Yong; Cai Xinyuan; Ji Ruifang
	2016-10
会议名称	ISCSLP 2016
会议录名称	ISCSLP 2016
会议日期	2016.10.17-2016.10.20
会议地点	Tian Jin, China
摘要	Speaker recognition is a valuable biometric recognition technology. Recently, with the development of deep learning, many deep network based speaker recognition algorithms are proposed. However, the evaluations on the speaker recognition algorithms are always performed on a small or middle scale of voiceprint corpus. There are few evaluation reports of speaker recognition on a large scale of voiceprint corpus. In this paper, we try to introduce a deep nonlinear metric learning based speaker identification algorithm and construct a larger scale of voiceprint corpus consisting of about 440 thousand people. We perform the evaluation of the deep nonlinear metric learning based method on the large scale corpus and give the recognition rate results in different scales. The evaluation results prove that, the performance is surely decreased when the scale of the corpus is increased. But for the scale of 400 thousand, the recognition rate of Top 50 is stable at about 95%, which means that it could be used in some real applications.
关键词	Speaker Identification Deep Nonlinear Metric Learning Large Scale Of Voiceprint Corpus
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/41083
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	Cai Xinyuan
推荐引用方式 GB/T 7714	Feng Yong,Cai Xinyuan,Ji Ruifang. Evaluation of the deep nonlinear metric learning based speaker identification on the large scale of voiceprint corpus[C],2016.