Anchor voiceprint recognition in live streaming via RawNet-SA and gated recurrent unit

EURASIP Journal on Audio, Speech, and Music Processing

Jiacheng Yao¹  Li Zhuo¹  Jing Zhang¹  Jiafeng Li¹ 

[1] Faculty of Information Technology, Beijing University of Technology, Beijing, China;Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China;

关键词: Voiceprint recognition;    Live streaming;    Anchor;    RawNet-SA;    GRU;   

DOI  :  10.1186/s13636-021-00234-3

来源: Springer

【 摘 要 】

With the sharp booming of online live streaming platforms, some anchors seek profits and accumulate popularity by mixing inappropriate content into live programs. After being blacklisted, these anchors even forged their identities to change the platform to continue live, causing great harm to the network environment. Therefore, we propose an anchor voiceprint recognition in live streaming via RawNet-SA and gated recurrent unit (GRU) for anchor identification of live platform. First, the speech of the anchor is extracted from the live streaming by using voice activation detection (VAD) and speech separation. Then, the feature sequence of anchor voiceprint is generated from the speech waveform with the self-attention network RawNet-SA. Finally, the feature sequence of anchor voiceprint is aggregated by GRU to transform into a deep voiceprint feature vector for anchor recognition. Experiments are conducted on the VoxCeleb, CN-Celeb, and MUSAN dataset, and the competitive results demonstrate that our method can effectively recognize the anchor voiceprint in video streaming.

【 授权许可】

CC BY