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.
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
