🧑‍🔬 Lay-Ki Soon

🏛️ Affiliations

🎓Monash University MalaysiaSubang Jaya · Malaysia2018–2026 · 48 papersEmployment since 2018 · Associate Head of School (Graduate Research), School of Information TechnologyEmployment 2018–2024 · Senior Lecturer, School of ITEmployment since 2024 · Associate Professor, School of Information Technologycurrent🎓Monash UniversityMelbourne · Australia2021–2026 · 9 paperscurrent🎓Multimedia UniversityMalacca · Malaysia2010–2019 · 46 papers🎓Soongsil UniversitySeoul · South Korea2007–2010 · 5 papers

🏛️Universiti Multimedia - Kampus CyberjayaCyberjaya · Malaysia2003–2018Employment 2003–2018 · Senior Lecturer, Faculty of Computing and Informatics

🏛️Soongsil UnviversitySeoul · South Korea2006–2009Education 2006–2009 · PhD in Engineering (Web Engineering), School of Computing

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Malaysian English News Decoded: A Linguistic Resource for Named Entity and Relation Extraction (2024 · 3 citations)
   Malaysian English (ME) is a local variety of English shaped by Malay, Chinese and Tamil. It contains borrowed words, mixed-language compounds and locally derived forms that confuse NER systems trained on Standard English. The authors first tested spaCy, Flair, Stanza and Malaya, all using OntoNotes 5.0-trained…
2. How well ChatGPT understand Malaysian English? An Evaluation on Named Entity Recognition and Relation Extraction (2023 · 2 citations)
   The paper asks whether ChatGPT can extract named entities and relations from Malaysian English, a variety shaped by Bahasa Malaysia, Chinese and Tamil.
3. Who You Are, What You Say: Intra- and Inter- Context Personality for Emotion Recognition in Conversation (2026)
   Emotion recognition in conversation (ERC) depends on both the dialogue context and who is speaking. Yet most systems merge all prior utterances into one context vector and represent speakers only superficially. The authors introduce PERC, a framework that brings personality into ERC. It first splits the history of a…

All works

6 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Can ChatGPT Perform Reasoning Using the IRAC Method in Analyzing Legal Scenarios Like a Lawyer? ↗Findings of the Association for Computational Linguistics: EMNLP 2023 · no summary yetXiaoxi Kang et al.2023 · 23 citations
2. Automating IRAC Analysis in Malaysian Contract Law using a Semi-Structured Knowledge Base ↗arXiv:2406.13217 · Artificial Intelligence and Law (2025) · no summary yetXiaoxi Kang et al.2024 · 12 citations
3. Malaysian English News Decoded: A Linguistic Resource for Named Entity and Relation ExtractionLanguage Resources and Evaluation Conference (LREC)Mohan Raj Chanthran, Lay-Ki Soon, Huey Fang Ong, et al.2024 · 3 citations
4. How well ChatGPT understand Malaysian English? An Evaluation on Named Entity Recognition and Relation ExtractionWorkshop on Generation, Evaluation and Metrics (GEM)Mohan Raj Chanthran, Lay-Ki Soon, Huey Fang Ong, et al.2023 · 2 citations
5. Who You Are, What You Say: Intra- and Inter- Context Personality for Emotion Recognition in ConversationFindings of the Association for Computational LinguisticsTazeek Bin Abdur Rakib, Lay-Ki Soon, Wern Han Lim2026
6. LePREC: Reasoning as Classification over Structured Factors for Assessing Relevance of Legal Issues ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetFanyu Wang et al.2026

🤝 Co-authors here

3 co-authors with a page, the most papers together first.

• Bhawani Selvaretnam ×2
• Huey Fang Ong ×2
• Mohan Raj Chanthran ×2

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• Workshop on Generation, Evaluation and Metrics (GEM): GEM 2023
• Language Resources and Evaluation Conference (LREC): LREC 2024
• Findings of the Association for Computational Linguistics: EMNLP 2023
• Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

🔗 Cited by

Papers of our library cite their works 24 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated 1 November 2026

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