Year: 2022
Type: preprint
Abstract: Target speaker extraction is to extract the target speaker, specified by enrollment utterance, in an environment with other competing speakers. Therefore, the task needs to solve two problems, speaker identification and separation, at the same time. In this paper, we combine self-attention and Recurrent Neural Networks (RNN). Further, we exploit various ways to combining different auxiliary information with mixed representations. Experimental results show that our proposed model achieves excellent performance on the task of target speaker extraction.
Source: arXiv (Cornell University)
Authors: Shen, Pengjie, He, Shulin, Zhang, Xueliang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4310745277