PI: Surangika Ranathunga
We propose to create a multi-domain Neural Machine Translation (NMT) System for Sinhala, Tamil, and English, the official languages of Sri Lanka.
PI: Nisansa de Silva
We propose to advance natural language processing for low-resource settings by leveraging data augmentation, transfer learning, and model adaptation techniques to overcome the scarcity of annotated data and linguistic resources.
PI: Nisansa de Silva
We propose to build and analyze Sinhala language resources, datasets, and models to strengthen NLP research for this low-resource language, while connecting it to English and Tamil through bilingual lexicons, embeddings, and cross-lingual methods.
Theses: MSc Major Component Research
Menan Velayuthan, "Multi-Domain Neural Machine Translation with Knowledge Distillation For Low Resource Languages", University of Moratuwa, 2025
Workshop Papers
Menan Velayuthan, Dilith Jayakody, Nisansa de Silva, Aloka Fernando, and Surangika Ranathunga, "Back to the Stats: Rescuing Low Resource Neural Machine Translation with Statistical Methods", in Proceedings of the Ninth Conference on Machine Translation, 2024, pp. 901--907. doi: 10.18653/v1/2024.wmt-1.87
