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.
PI: Nisansa de Silva
We propose to advance social media text analysis by combining linguistic study, preprocessing, and deep learning models to better capture sentiment, structure, and meaning in informal, large-scale user-generated text.
Journal Papers
Krishan Chavinda, Pasan Kalansooriya, Thushalya Weerasuriya, Nisansa de Silva, Uthayasanker Thayasivam, Kogul Srikandabala, Kirishnni Prabagar, and Damminda Alahakoon, "An emotion aware context adaptive machine learning approach for detecting hate speech in social media", Neural Computing and Applications, vol. 38, no. 8, pp. 1433-3058, 2026. doi: 10.1007/s00521-026-12029-8
W M Yomal De Mel and Nisansa de Silva, "Linguistic Analysis of Sinhala YouTube Comments on Sinhala Music Videos: A Dataset Study", ICTer, vol. 18, no. 2, pp. 121-130, 2025. doi: 10.4038/icter.v18i2.7299
Conference Papers
Yomal De Mel and Nisansa de Silva, "GeeSanBhava: Sentiment Tagged Sinhala Music Video Comment Data Set", in International Conference on Computational Collective Intelligence, 2025, pp. 157--171. doi: 10.1007/978-3-032-10209-6_11
