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Disentangling Singlish Discourse Particles with Task-Driven Representation

2024/09/30 by Linus Tze En Foo, Lynnette Hui Xian Ng, Foo, Linus Tze En +1 · 2 citations
Computer Science · #Topic Modeling #Natural Language Processing Techniques

paper · pdf · doi:10.48550/arxiv.2409.20366

Abstract

Singlish, or formally Colloquial Singapore English, is an English-based creole language originating from the SouthEast Asian country Singapore. The language contains influences from Sinitic languages such as Chinese dialects, Malay, Tamil and so forth. A fundamental task to understanding Singlish is to first understand the pragmatic functions of its discourse particles, upon which Singlish relies heavily to convey meaning. This work offers a preliminary effort to disentangle the Singlish discourse particles (lah, meh and hor) with task-driven representation learning. After disentanglement, we cluster these discourse particles to differentiate their pragmatic functions, and perform Singlish-to-English machine translation. Our work provides a computational method to understanding Singlish discourse particles, and opens avenues towards a deeper comprehension of the language and its usage.

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