README.md

metadata

license: cc-by-sa-4.0
arxiv: 2601.14046
dataset_info:
  features:
    - name: speaker
      dtype: string
    - name: text
      dtype: string
    - name: accent
      dtype: string
    - name: raw_accent
      dtype: string
    - name: gender
      dtype: string
    - name: l1
      dtype: string
    - name: audio
      dtype:
        audio:
          decode: false
    - name: duration_sec
      dtype: float64
    - name: accent_cluster
      dtype: string
  splits:
    - name: train
      num_bytes: 1365255727
      num_examples: 6917
    - name: validation
      num_bytes: 498376566
      num_examples: 2525
    - name: test
      num_bytes: 1084980589
      num_examples: 5497
  download_size: 3468541402
  dataset_size: 2948612882
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*

EdAcc

The Edinburgh International Accents of English Corpus (EdAcc) is a speech dataset designed to evaluate automatic speech recognition (ASR) systems on a wide range of global English accents.

Citation

@inproceedings{sanabria23edacc,
   title="{The Edinburgh International Accents of English Corpus: Towards the Democratization of English ASR}",
   author={Sanabria, Ramon and Bogoychev, Nikolay and  Markl, Nina and Carmantini, Andrea and  Klejch, Ondrej and Bell, Peter},
   booktitle={ICASSP 2023},
   year={2023},
}

You can use this dataset with our benchmarking toolkit at https://github.com/changelinglab/prism

@misc{prism2026,
      title={PRiSM: Benchmarking Phone Realization in Speech Models}, 
      author={Shikhar Bharadwaj and Chin-Jou Li and Yoonjae Kim and Kwanghee Choi and Eunjung Yeo and Ryan Soh-Eun Shim and Hanyu Zhou and Brendon Boldt and Karen Rosero Jacome and Kalvin Chang and Darsh Agrawal and Keer Xu and Chao-Han Huck Yang and Jian Zhu and Shinji Watanabe and David R. Mortensen},
      year={2026},
      eprint={2601.14046},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2601.14046}, 
}

License

This dataset is released under the CC BY-SA 4.0 license.

Source

Official dataset website: https://doi.org/10.7488/ds/7914