Leveraging in-the-wild Data for Effective Self-supervised Pretraining in Speaker Recognition-Reference-Cited by-同舟云学术

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Leveraging in-the-wild Data for Effective Self-supervised Pretraining in Speaker Recognition

Published:2024-04-14 Issue: Volume:30 Page:10901-10905
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Wang Shuai¹,Bai Qibing¹,Liu Qi²,Yu Jianwei²,Chen Zhengyang³,Han Bing³,Qian Yanmin³,Li Haizhou⁴

Affiliation:

1. Shenzhen Research Institute of Big Data,Shenzhen,China

2. Tencent,Shenzhen,China

3. Shanghai Jiao Tong University,Shanghai,China

4. The Chinese University of Hong Kong,School of Data Science,Shenzhen (CUHK-Shenzhen),China

Funder

Shenzhen Research Institute of Big Data

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447489.pdf?arnumber=10447489

Reference28 articles.

1. VoxCeleb: A Large-Scale Speaker Identification Dataset

2. VoxCeleb2: Deep Speaker Recognition

3. CN-Celeb: A Challenging Chinese Speaker Recognition Dataset

4. CN-Celeb: Multi-genre speaker recognition

5. WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

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