mlsanityData to 14 Oct 2026

What shall we do with an hour of data? Speech recognition for the un- and under-served languages of Common Voice

arXiv 2105.04674 ↗First posted 10 May 2021cs.CL cs.LG cs.SDcited by 5

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Abstract (arXiv)

This technical report describes the methods and results of a three-week sprint to produce deployable speech recognition models for 31 under-served languages of the Common Voice project. We outline the preprocessing steps, hyperparameter selection, and resulting accuracy on official testing sets. In addition to this we evaluate the models on multiple tasks: closed-vocabulary speech recognition, pre-transcription, forced alignment, and key-word spotting. The following experiments use Coqui STT, a toolkit for training and deployment of neural Speech-to-Text models.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 3 of its 10 references that are in the map. First posted on arXiv 10 May 2021.

Builds on

3 of 10 references.

References · 3

  1. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,384
  2. 2019SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognitioncited by 1,380
  3. 2021Few-Shot Keyword Spotting in Any Languagecited by 27

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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 1; 2025: 1.

5 papers.