Speaker Identification Based On Ivector And Xvector. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Yuan, Xinyu; Li, Guanyu; Han, Jiao; Wang, Di; Tiankai, Zhi
• Is Part Of: Journal of physics. Volume 1827:Issue 1(2021)
• Publication Date: 2021-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1827/1/012133
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: As an important branch of AI (Artificial Intelligence), speaker recogniti-on technology has developed rapidly in recent years. At present, speaker recognition technologies based on traditional methods and deep learning methods are very mature and have achieved good results. As a key technology in human-machine voice intera-ction, speaker recognition has changed human life in many ways. However, there is almost no research on speaker recognition in Tibetan. This paper uses Gaussian mix-ture model and deep neural network TDNN as the theoretical basis. On the Tibetan language corpus, the speaker identification on the ivector of GMM-UBM and the speaker identification on the xvector of TDNN are performed respectively, and the experimental results are compared. The experimental system is divided into prepro-cessing, feature extraction, model training and decision.