Disentangling Singlish Discourse Particles with Task-Driven Representation

• URL: http://arxiv.org/abs/2409.20366v4
• Date: Wed, 16 Oct 2024 15:09:14 GMT
• Title: Disentangling Singlish Discourse Particles with Task-Driven Representation
• Authors: Linus Tze En Foo, Lynnette Hui Xian Ng,
• Abstract summary: Singlish, or formally Colloquial Singapore English, is an English-based creole language originating from the SouthEast Asian country Singapore. A fundamental task to understanding Singlish is to first understand the pragmatic functions of its discourse particles. This work offers a preliminary effort to disentangle the Singlish discourse particles with task-driven representation learning. After disentanglement, we cluster these discourse particles to differentiate their pragmatic functions, and perform Singlish-to-English machine translation.
• Score: 1.3812010983144802
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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