Comparative Analysis of Deep Learning Models for Part of Speech Tagging in the Malay Language
Bakare Mustaphaa Adebayo,
Kalaiarasi Sonai Muthu Anbananthen,
Saravanan Muthaiyah
et al.
Abstract:Despite the widespread use of Malay, under-resourced languages like Malay face challenges in Natural Language Processing (NLP), particularly in Part-of-Speech (POS) tagging. The scarcity of annotated corpora poses a primary obstacle to POS tagging in Malay. This study aims to enhance the effectiveness and reliability of POS tagging models explicitly tailored for under-resourced languages within the field of NLP, focusing on Malay. Existing models, which rely on Conditional Random Fields and Hidden Markov Model… Show more
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