Self-Supervised Learning Representations for Dialect Identification with Sparse Transformers-Reference-Cited by-同舟云学术

Self-Supervised Learning Representations for Dialect Identification with Sparse Transformers

Published:2024-01-26 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 8th International Conference on Control Engineering and Artificial Intelligence
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Author:

Shen Ran¹^ORCID,Li Yiling¹^ORCID,Gu Hongjie¹^ORCID,Wang Yifan¹^ORCID,Huang Junjie²^ORCID,She Qingshun²^ORCID

Affiliation:

1. Marketing Service Center, State Grid Zhejiang Electric Power Co., Ltd., China

2. College of Computer Science and Technology, Zhejiang University, China

Funder

Zhejiang Electric Power Co., Ltd.

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3640824.3640825

Reference31 articles.

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3. Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems 33 (2020), 12449–12460.

4. Utterance-level End-to-end Language Identification Using Attention-based CNN-BLSTM

5. Alexis Conneau, Alexei Baevski, Ronan Collobert, Abdelrahman Mohamed, and Michael Auli. 2020. Unsupervised cross-lingual representation learning for speech recognition. arXiv preprint arXiv:2006.13979 (2020).