An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus

• Published in: Majallat Baghdād lil-ʻulūm Vol. 21; no. 2(SI); p. 622
• Main Authors: Kang, Di-Wen, Ye, Shao-Qiang, Syed Ahmad, Sharifah Zarith Rahmah, Mo, Li-Ping, Qin, Feng, Zhou, Pan
• Format: Journal Article
• Language: English
• Published: University of Baghdad, College of Science for Women 01.01.2024
• Subjects: Harmony Search Algorithm, Low-resource language, Optimization, Part-of-Speech tagging, Unknown words
• ISSN: 2078-8665; 2411-7986
• DOI: 10.21123/bsj.2024.9694

Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.