research-article

A Neural Joint Model with BERT for Burmese Syllable Segmentation, Word Segmentation, and POS Tagging

Authors:

Shengxiang Gao,

Hongbin WangAuthors Info & Claims

Transactions on Asian and Low-Resource Language Information Processing, Volume 20, Issue 4

Article No.: 54, Pages 1 - 23

https://doi.org/10.1145/3436818

Published: 26 May 2021 Publication History

Abstract

The smallest semantic unit of the Burmese language is called the syllable. In the present study, it is intended to propose the first neural joint learning model for Burmese syllable segmentation, word segmentation, and part-of-speech (POS) tagging with the BERT. The proposed model alleviates the error propagation problem of the syllable segmentation. More specifically, it extends the neural joint model for Vietnamese word segmentation, POS tagging, and dependency parsing [28] with the pre-training method of the Burmese character, syllable, and word embedding with BiLSTM-CRF-based neural layers. In order to evaluate the performance of the proposed model, experiments are carried out on Burmese benchmark datasets, and we fine-tune the model of multilingual BERT. Obtained results show that the proposed joint model can result in an excellent performance.

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Cited By

Santiago-Benito HCórdova-Esparza DCastro-Sánchez NTerven JRomero-González JGarcía-Ramirez T(2025)Automatic grammatical tagger for a Spanish–Mixtec parallel corpusSoftwareX10.1016/j.softx.2024.10198529(101985)Online publication date: Feb-2025
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Wen YXian YWang YYu Z(2024)UnifiedCut: A Simple and Efficient Neural Model for Thai, Burmese and Khmer Word SegmentationApplied Sciences10.3390/app14231143514:23(11435)Online publication date: 9-Dec-2024
https://doi.org/10.3390/app142311435
Jayanth KBharathi Mohan GKumar R(2023)Indian Language Analysis with XLM-RoBERTa: Enhancing Parts of Speech Tagging for Effective Natural Language Preprocessing2023 Seventh International Conference on Image Information Processing (ICIIP)10.1109/ICIIP61524.2023.10537689(850-854)Online publication date: 22-Nov-2023
https://doi.org/10.1109/ICIIP61524.2023.10537689
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Index Terms

A Neural Joint Model with BERT for Burmese Syllable Segmentation, Word Segmentation, and POS Tagging
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
    2. Robotics
2. Networks
  1. Network properties
    1. Network reliability

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 20, Issue 4

July 2021

419 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3465463

Editor:
Imed Zitouni
Google, USA

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Copyright © 2021 Association for Computing Machinery.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 26 May 2021

Accepted: 01 November 2020

Revised: 01 July 2020

Received: 01 March 2020

Published in TALLIP Volume 20, Issue 4

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Key Program of National Natural Science Foundation of China
National Natural Science Foundation of China
Key Project of Natural Science Foundation of Yunnan Province
Candidates of the Young and Middle Aged Academic and Technical Leaders of Yunnan Province

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Cited By

Santiago-Benito HCórdova-Esparza DCastro-Sánchez NTerven JRomero-González JGarcía-Ramirez T(2025)Automatic grammatical tagger for a Spanish–Mixtec parallel corpusSoftwareX10.1016/j.softx.2024.10198529(101985)Online publication date: Feb-2025
https://doi.org/10.1016/j.softx.2024.101985
Wen YXian YWang YYu Z(2024)UnifiedCut: A Simple and Efficient Neural Model for Thai, Burmese and Khmer Word SegmentationApplied Sciences10.3390/app14231143514:23(11435)Online publication date: 9-Dec-2024
https://doi.org/10.3390/app142311435
Jayanth KBharathi Mohan GKumar R(2023)Indian Language Analysis with XLM-RoBERTa: Enhancing Parts of Speech Tagging for Effective Natural Language Preprocessing2023 Seventh International Conference on Image Information Processing (ICIIP)10.1109/ICIIP61524.2023.10537689(850-854)Online publication date: 22-Nov-2023
https://doi.org/10.1109/ICIIP61524.2023.10537689
Guven Z(2022)The Comparison of Language Models with a Novel Text Filtering Approach for Turkish Sentiment AnalysisACM Transactions on Asian and Low-Resource Language Information Processing10.1145/355789222:2(1-16)Online publication date: 27-Dec-2022
https://dl.acm.org/doi/10.1145/3557892
Jin YTao SLiu QLiu X(2022)A BiLSTM-CRF Based Approach to Word Segmentation in Chinese2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927991(1-4)Online publication date: 12-Sep-2022
https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927991

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