Researchers at IISc’s SPIRE Lab, in collaboration with ARTPARK and Google, have released SraVaani, the first multilingual Indian speech recognition model trained on 65 Indian languages and dialects, including over 40 languages that today’s speech recognition systems do not officially support.
Designed to take speech AI beyond scheduled languages, SraVaani extends automatic speech recognition to several regional and non-scheduled Indian languages that remain underserved by existing speech technology. The model is freely and publicly available on Hugging Face under an MIT licence.
Bridging a gap
While most speech AI systems work effectively in only a handful of dominant languages, leaving many of the languages and dialects spoken across India without reliable speech-to-text capabilities, SraVaani addresses this gap.
It has addressed this gap by covering 20 scheduled languages and 45 regional languages and dialects, potentially opening speech AI capabilities to around 25 crore people as per the 2011 Census whose languages are not properly handled by current systems.
Its coverage is designed to be pan-India, spanning 19 languages from the Northeast, 16 from eastern India, nine from the west, eight from the north, six from the south and five from central India, along with English and Sanskrit. The model supports languages such as Garo, Angika, Chakma, Kokborok, Tulu, Bundeli and Bajjika, taking Indian dialect speech-to-text and regional-language AI beyond the languages traditionally prioritised by speech technology.
Error rate
Results on several of these languages are particularly strong, including a 9.5% word error rate on Garo, compared with 69.4% for the next-best system evaluated.
“As India builds its own capabilities in artificial intelligence, inclusive language technology must be part of that ambition. At IISc, research has always been in service to the nation, and SraVaani, serving more than 60 Indian languages, is a contribution toward that,” said Govindan Rangarajan, Director, IISc.
Published - August 13, 2026 06:49 pm IST