ActivePI: 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.
ActivePI: 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.
Conference Papers
Yomal De Mel, Kasun Wickramasinghe, Nisansa de Silva, and Surangika Ranathunga, "Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq Approaches", in Proceedings of the First Workshop on Natural Language Processing for Indo-Aryan and Dravidian Languages, 2025, pp. 166--173.
