mlsanityData to 14 Oct 2026

Bengali Common Voice Speech Dataset for Automatic Speech Recognition

arXiv 2206.14053 ↗First posted 28 Jun 2022cs.CL cs.SD eess.AScited by 6

Not on the map. Why?

Abstract (arXiv)

Bengali is one of the most spoken languages in the world with over 300 million speakers globally. Despite its popularity, research into the development of Bengali speech recognition systems is hindered due to the lack of diverse open-source datasets. As a way forward, we have crowdsourced the Bengali Common Voice Speech Dataset, which is a sentence-level automatic speech recognition corpus. Collected on the Mozilla Common Voice platform, the dataset is part of an ongoing campaign that has led to the collection of over 400 hours of data in 2 months and is growing rapidly. Our analysis shows that this dataset has more speaker, phoneme, and environmental diversity compared to the OpenSLR Bengali ASR dataset, the largest existing open-source Bengali speech dataset. We present insights obtained from the dataset and discuss key linguistic challenges that need to be addressed in future versions. Additionally, we report the current performance of a few Automatic Speech Recognition (ASR) algorithms and set a benchmark for future research.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 3 of its 44 references that are in the map. First posted on arXiv 28 Jun 2022.

Builds on

3 of 44 references.

References · 3

  1. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,384
  2. 2020A Large Multi-Target Dataset of Common Bengali Handwritten Graphemescited by 12
  3. 2020Synthetic Error Dataset Generation Mimicking Bengali Writing Patterncited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 0; 2024: 1; 2025: 0; 2026: 1.

6 papers.