This paper presents the project we did to develop a corpus, which is continuously updating, dynamic and covers a wide range of topics for Sinhala language. This paper will introduce the technologies we have used in the project and will discuss its design features.
Keywords: Natural Language Processing | Big Data | Sinhala | Corpus | Corpus Linguistics | Language Corpus |
@inproceedings{upeksha2015implementing,
title={{Implementing a Corpus for Sinhala Language}},
author={Upeksha, Dimuthu and Wijayarathna, Chamila and Siriwardena, Maduranga and Lasandun, Lahiru and Wimalasuriya, Chinthana and De Silva, N. H. N. D. and Dias, Gihan},
booktitle={Symposium on Language Technology for South Asia 2015},
year={2015},
abstract={This paper presents the project we did to develop a corpus, which is continuously updating, dynamic and covers a wide range of topics for Sinhala language. This paper will introduce the technologies we have used in the project and will discuss its design features.},
misc={https://goo.gl/Wp9e28,NLP:BIG:SIN,https://i1.rgstatic.net/publication/306264442_Implementing_a_Corpus_for_Sinhala_Language/links/57b5adce08aede8a665ba954/largepreview.png},
doi={10.13140/RG.2.2.23035.11047}
}
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.