Chang-Uk Shin


2024

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This Word Mean What: Constructing a Singlish Dictionary with ChatGPT
Siew Yeng Chow | Chang-Uk Shin | Francis Bond
Proceedings of the 2nd Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia (EURALI) @ LREC-COLING 2024

Despite the magnitude of recent progress in natural language processing and multilingual language modeling research, the vast majority of NLP research is focused on English and other major languages. This is because recent NLP research is mainly data-driven, and there is more data for resource-rich languages. In particular, Large Language Models (LLM) make use of large unlabeled datasets, a resource that many languages do not have. In this project, we built a new, open-sourced dictionary of Singlish, a contact variety that contains features from English and other local languages and is syntactically, phonologically and lexically distinct from Standard English (Tan, 2010). First, a list of Singlish words was extracted from various online sources. Then using an open Chat-GPT LLM API, the description, including the defintion, part of speech, pronunciation and examples was produced. These were then refined through post processing carried out by a native speaker. The dictionary currently has 1,783 entries and is published under the CC-BY-SA license. The project was carried out with the intention of facilitating future Singlish research and other applications as the accumulation and management of language resources will be of great help in promoting research on the language in the future.

2017

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Building a Better Bitext for Structurally Different Languages through Self-training
Jungyeul Park | Loïc Dugast | Jeen-Pyo Hong | Chang-Uk Shin | Jeong-Won Cha
Proceedings of the First Workshop on Curation and Applications of Parallel and Comparable Corpora

We propose a novel method to bootstrap the construction of parallel corpora for new pairs of structurally different languages. We do so by combining the use of a pivot language and self-training. A pivot language enables the use of existing translation models to bootstrap the alignment and a self-training procedure enables to achieve better alignment, both at the document and sentence level. We also propose several evaluation methods for the resulting alignment.