@article{kumar-etal-2026-singlish,
    title = "{S}inglish to {E}nglish Translation with Precision: A Dataset and Language Detection-Driven Masked Modeling for {S}inglish to {E}nglish Translation",
    author = "Kumar, Sujit  and
      Ang, Gerome Kusuma  and
      Ma, Stephanie Hilary Xinyi  and
      Ho, Andy Hau Yan  and
      Khong, Andy",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.280/",
    pages = "3506--3516",
    abstract = "Singlish, a creole rooted in English and influenced by Singapore{'}s multilingual and multicultural environment, poses significant challenges for those proficient in standard English due to its unique and often complex lexical and syntactic structures. Despite significant advancements in language translation for both high- and low-resource languages, translating Singlish to English remains largely underexplored. This gap is primarily due to the lack of dedicated datasets for language detection and Singlish-to-English translation, as well as the absence of robust models capable of addressing the unique linguistic challenges posed by Singlish. In this work, we curate a word-level language detection dataset, a Singlish-to-English translation dataset, and propose a Language Detection-driven Masked Language Modelling approach for translating Singlish into English. We evaluate the performance of existing models and the proposed approach on two Singlish-to-English translation datasets, including our proposed SEAT dataset. The results demonstrate that the proposed LD-MLMTrans approach outperforms the baseline model and exhibits high proficiency in Singlish-to-English translation."
}