A search engine for Tumakuru dialect: IIIT-B team develops AI interface for colloquial Kannada Premium
The Hindu
Access to information is relatively easy for the city dweller for whom knowledge is at the tip of the finger. Not so much is the case beyond the urban boundaries.
Access to information is relatively easy for the city dweller for whom knowledge is at the tip of the finger. Not so much is the case beyond the urban boundaries.
Rural communities frequently depend on community radio, neighbourhood newspapers, and volunteer organisations for hyper-local information. But the corpus of knowledge produced by these entities often remains localised and is absent on the internet making it difficult for the people to re-access it. Added to this are the language challenges.
Students of International Institute of Information Technology-Bangalore (IIIT-B) have devised a solution for this by developing a search interface for colloquial audio content in Kannada language.
Called Graama-Kannada Audio Search, the interface allows the user to search for and access hyperlocal information from the Tumakuru region in audio format.
The framework was developed by Sharath Srivatsa (PhD Scholar, IIIT-B), Aparna M. (M.S. by Research Scholar, IIIT-B) and Sai Madhavan G. (iMTECH student, IIIT-B) under the guidance of Srinath Srinivasa (Professor and Dean (R&D), Web Science Lab, IIIT-B) and with the help of T. B. Dinesh (iruWay Rural Research Lab, Janastu).
Namma Halli Radiois a community owned WiFimesh radio run by Janastu NGO in the Tumakuru region. Over the years the radio grew an audio corpus rich with information on local customs, cultures, festivals, Covid-19 awareness and so on. But the absence of this data on the internet meant that people could not access the information at a later stage.
The IIIT-B team worked with the community radio and fed the latter’s audio corpus into their search model. The audio was transcribed into text using automatic speech recognition (ASR) models. When a user searches for a certain keyword, this transcribed text would be matched with it to deliver results.
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