Punctuation Prediction in Vietnamese ASRs Using Transformer-Based Models

Author:

Bui Viet The,Tran Oanh ThiORCID

Publisher

Springer International Publishing

Reference26 articles.

1. Alam, T., Khan, A., Alam, F.: Punctuation restoration using transformer models for high-and low-resource languages. In: Proceedings of the 2020 EMNLP Workshop W-NUT: The Sixth Workshop on Noisy User-Generated Text. Association for Computational Linguistics, pp. 132–142 (2020)

2. Ballesteros, M., Wanner, L.: A neural network architecture for multilingual punctuation generation. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, Texas, 1–5 November, pp. 1048–1053 (2016)

3. Bui, V.T., Tran, O.T., Le, P.H.: Improving sequence tagging for Vietnamese text using transformer-based neural models. In: Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, pp. 13–20 (2020)

4. Che, X., Wang, C., Yang, H., Meinel, C.: Punctuation prediction for unsegmented transcript based on word vector. In: The 10th International Conference on Language Resources and Evaluation (LREC), pp. 654–658 (2016)

5. Cho, E., Niehues, J., Kilgour, K., Waibel, A.: Punctuation insertion for real-time spoken language translation. In: Proceedings of the Eleventh International Workshop on Spoken Language Translation (2015)

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1. Towards Developing an Automatic Punctuation Prediction Model for Bangla Language: A Pre-trained Mono-lingual Transformer-based Approach;2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT);2024-05-02

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