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
This project delves into the synergy between Natural Language Processing (NLP) and the legal domain, presenting novel solutions to enduring challenges.
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.
Melonie de Almeida, Chamodi Samarawickrama, Nisansa de Silva, Gathika Ratnayaka, and Amal Shehan Perera, "Legal Party Extraction from Legal Opinion Text with Sequence to Sequence Learning", in 2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer), 2020, pp. 143--148. doi: 10.1109/ICTer51097.2020.9325488
