mlsanityData to 7 Oct 2026

A Toolbox for Construction and Analysis of Speech Datasets

arXiv 2104.04896 ↗First posted 11 Apr 2021eess.AS cs.CL cs.SDcited by 5

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Abstract (arXiv)

Automatic Speech Recognition and Text-to-Speech systems are primarily trained in a supervised fashion and require high-quality, accurately labeled speech datasets. In this work, we examine common problems with speech data and introduce a toolbox for the construction and interactive error analysis of speech datasets. The construction tool is based on K"urzinger et al. work, and, to the best of our knowledge, the dataset exploration tool is the world's first open-source tool of this kind. We demonstrate how to apply these tools to create a Russian speech dataset and analyze existing speech datasets (Multilingual LibriSpeech, Mozilla Common Voice). The tools are open sourced as a part of the NeMo framework.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 17 of its 37 references that are in the map. First posted on arXiv 11 Apr 2021.

Builds on

17 of 37 references.

References · 17

  1. 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,838
  2. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,358
  3. 2020MLS: A Large-Scale Multilingual Dataset for Speech Researchcited by 467
  4. 2017AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition Baselinecited by 364
  5. 2014Deep Speech: Scaling up end-to-end speech recognitioncited by 354
  6. 2019NeMo: a toolkit for building AI applications using Neural Modulescited by 230
  7. 2017State-of-the-art Speech Recognition With Sequence-to-Sequence Modelscited by 196
  8. 2018AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scalecited by 125
  9. 2020ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Contextcited by 96
  10. 2019QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutionscited by 93
  11. 2021SPGISpeech: 5,000 hours of transcribed financial audio for fully formatted end-to-end speech recognitioncited by 77
  12. 2019Jasper: An End-to-End Convolutional Neural Acoustic Modelcited by 75
5 more
  1. 2020CTC-Segmentation of Large Corpora for German End-to-end Speech Recognitioncited by 75
  2. 2021Hi-Fi Multi-Speaker English TTS Datasetcited by 60
  3. 2019CSS10: A Collection of Single Speaker Speech Datasets for 10 Languagescited by 54
  4. 2016Wav2Letter: an End-to-End ConvNet-based Speech Recognition Systemcited by 43
  5. 2021Citrinet: Closing the Gap between Non-Autoregressive and Autoregressive End-to-End Models for Automatic Speech Recognitioncited by 33

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 2.

5 papers.

  1. 2023SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappingscited by 4
  2. 2025Synthetic Voice Data for Automatic Speech Recognition in African Languagescited by 3
  3. 2022Building and curating conversational corpora for diversity-aware language science and technologycited by 2
  4. 2026Task-Lens: Cross-Task Utility Based Speech Dataset Profiling for Low-Resource Indian Languagescited by 0
  5. 2026GigaAM Multilingual: Foundation Model for Underrepresented Languagescited by 0