An efficient transformer-based model for Vietnamese punctuation prediction

• Main Authors: TRAN, Hieu, DINH, Cuong V., PHAM, Hong Quang, NGUYEN, Binh T.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Punctuation prediction; Transfer learning; Transformer models; Numerical Analysis and Computation; South and Southeast Asian Languages and Societies; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/7102; https://ink.library.smu.edu.sg/context/sis_research/article/8105/viewcontent/Tran2021_AnEfficientTransformer_Vietnamese_pv.pdf
• Institution: Singapore Management University

In both formal and informal texts, missing punctuation marks make the texts confusing and challenging to read. This paper aims to conduct exhaustive experiments to investigate the benefits of the pre-trained Transformer-based models on two Vietnamese punctuation datasets. The experimental results sh...