AI & ML interests

Neural Machine Translation, Sentence Boundary Disambiguation, Automatic Cognate Detection, Phylogenetic Tree Inference

Recent Activity

Organization Card

Digital Techniques for Language Revival

We explore how technology can support comparative linguistics, language education, and the revitalisation and revival of languages.

Aims

  • NMT model training
  • Corpus building
  • Bridging pedagogy and typology

Current Study: Sentence-Level Corpus for Arem

Our current study focuses on documenting the critically endangered Arem language. We are developing a smartphone app to record sentences and support fieldwork to build a parallel corpus in English, Vietnamese, and Arem. By collecting language at the sentence level, the project aims to capture context and usage beyond word lists alone.

The resulting corpus will support research into Arem grammar, the creation of a dictionary with example sentences showing how words are used, and the development of neural machine translation models.