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Vakyansh: ASR Toolkit for Low Resource Indic languages (2203.16512v2)

Published 30 Mar 2022 in cs.CL and eess.AS

Abstract: We present Vakyansh, an end to end toolkit for Speech Recognition in Indic languages. India is home to almost 121 languages and around 125 crore speakers. Yet most of the languages are low resource in terms of data and pretrained models. Through Vakyansh, we introduce automatic data pipelines for data creation, model training, model evaluation and deployment. We create 14,000 hours of speech data in 23 Indic languages and train wav2vec 2.0 based pretrained models. These pretrained models are then finetuned to create state of the art speech recognition models for 18 Indic languages which are followed by LLMs and punctuation restoration models. We open source all these resources with a mission that this will inspire the speech community to develop speech first applications using our ASR models in Indic languages.

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Authors (7)
  1. Harveen Singh Chadha (10 papers)
  2. Anirudh Gupta (9 papers)
  3. Priyanshi Shah (10 papers)
  4. Neeraj Chhimwal (8 papers)
  5. Ankur Dhuriya (8 papers)
  6. Rishabh Gaur (7 papers)
  7. Vivek Raghavan (14 papers)
Citations (11)

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