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
Vihanga Jayawickrama, Gihan Weeraprameshwara, Nisansa de Silva, and Yudhanjaya Wijeratne, "Facebook for Sentiment Analysis: Baseline Models to Predict Facebook Reactions of Sinhala Posts", The International Journal on Advances in ICT for Emerging Regions, vol. 15, no. 2, 2022. doi: 10.4038/icter.v15i2.7248
Conference Papers
Vihanga Jayawickrama, Gihan Weeraprameshwara, Nisansa de Silva, and Yudhanjaya Wijeratne, "Seeking Sinhala Sentiment: Predicting Facebook Reactions of Sinhala Posts", in 2021 21st International Conference on Advances in ICT for Emerging Regions (ICter), 2021, pp. 177-182. doi: 10.1109/ICter53630.2021.9774796 
