mlsanityData to 14 Oct 2026

Vakyansh: ASR Toolkit for Low Resource Indic languages

arXiv 2203.16512 ↗First posted 30 Mar 2022cs.CL eess.AScited by 7

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Abstract (arXiv)

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 language models 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.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 6 of its 18 references that are in the map. First posted on arXiv 30 Mar 2022.

Builds on

6 of 18 references.

References · 6

  1. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,905
  2. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
  3. 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,488
  4. 2021Multilingual and code-switching ASR challenges for low resource Indian languagescited by 53
  5. 2021CLSRIL-23: Cross Lingual Speech Representations for Indic Languagescited by 22
  6. 2021Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling Insightscited by 14

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 0; 2025: 0; 2026: 6.

7 papers.