A Cross-lingual part-of-speech tagging for Malay language

• Published in: ICAART 2015 - 7th International Conference on Agents and Artificial Intelligence, Proceedings
• Main Author: Zamin N.; Bakar Z.A.
• Format: Conference paper
• Language: English
• Published: SciTePress 2015
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943278386&doi=10.5220%2f0005150602320240&partnerID=40&md5=de92cd6de1750dbe2a4450930a83396d

Cross-lingual annotation projection methods can benefit from rich-resourced languages to improve the performance of Natural Language Processing (NLP) tasks in less-resourced languages. In this research, Malay is experimented as the less-resourced language and English is experimented as the rich-resourced language. The research is proposed to reduce the deadlock in Malay computational linguistic research due to the shortage of Malay tools and annotated corpus by exploiting state-of-the-art English tools. This paper proposed a cross-lingual annotation projection based on word alignment of two languages with syntactical differences. A word alignment method known as MEWA (Malay-English Word Aligner) that integrates a Dice Coefficient and bigram string similarity measure is proposed. MEWA is experimented to automatically induced annotations using a Malay test collection on terrorism and an identified English tool. In the POS annotation projection experiment, the algorithm achieved accuracy rate of 79%.