IndicNLP project focuses on building an knowledge management framework for oral community knowledge in low-resource and colloquial Kannada language.
Background
Knowledge in rural communities is largely created, preserved, and is transferred verbally, and it is limited. This information is valuable to these communities, and managing and making it available digitally with state-of-the-art approaches enriches awareness and collective knowledge of people of these communities. The large amounts of data and information produced on the Internet are inaccessible to the population in these rural communities due to factors like lack of infrastructure, connectivity, and limited literacy. Knowledge internal to rural communities is also not conserved and made available in any global Big Data information systems. Artificial Intelligence (AI) technologies such as Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) provide substantial assistance when vast quantities of data, like Big Data, are available to build solutions. In the case of low-resource languages like Kannada and rural colloquial dialects, publicly available corpora are significantly less. Building state-of-the-art AI solutions is challenging in this context, and we address this problem in this work. Knowledge management in rural communities requires a low-cost and efficient approach that social workers can use. Organizations such as Namma Halli Radio have collected an audio corpus of a few hours containing community interactions spoken in colloquial language. We propose an architecture for oral knowledge management for rural communities speaking colloquial Kannada using audio recordings.
Funding Agency
Mphasis F1 foundation
Publications
M. Aparna, Sharath Srivatsa, G. Sai Madhavan, T. B. Dinesh, and Srinath Srinivasa. AI-based Assistance for Management of Oral Community Knowledge in Low-Resource and Colloquial Kannada language. International Conference on Big-Data-Analytics in Astronomy, Science and Engineering, BASE 2023, Springer LNCS. [to-appear]
Sharath Srivatsa, Aparna M, Sai Madhavan G, and Srinath Srinivasa. 2024. Knowledge Management Framework Over Low Resource Indian Colloquial Language Audio Contents. In Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD) (CODS-COMAD ’24). Association for Computing Machinery, New York, NY, USA, 553–557. https://doi.org/10.1145/3632410.3632483
Aparna M and Srinath Srinivasa. 2023. Active learning for Named Entity Recognition in Kannada. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.24580582.v1
Media Mentions
- The New Indian Express : IIIT-B students develop web search in colloquial Kannada
- The Hindu – Online : A search engine for Tumakuru dialect: IIIT-B team develops AI interface for colloquial Kannada
- The New Indian Express – Edex Live: IIIT Bengaluru students develop web search in colloquial Kannada using community radio
- The Times of India – Bangalore Mirror: Sound Garden – State-of-the-art Automatic Speech Recognition
Demo
Graama-Kannada Audio Search webapp : http://103.156.19.244:33035/,
(username : guest, password : guest123)
Graama-Kannada demo video:
People
Research Scholars
Project Students
- Goutham U R
- Ram Sai Koushik Polisetti
- Sai Madhavan G
- Kappagantula Lakshmi Abhigna
- Manuj Malik
- Debmalya Sen
- Vikram Adithya C P
- Venumula Sai Sumanth Reddy
