LetTokenBurn
Sign in
Auto71%Harbor: pendingMultilingual

Common Voice15

CommonVoice15 Scenario The most recent release of CommonVoice15 (Ardila et al, 2019) includes 114 languages.

PaperRepoDataset

How to run

ltb · common-voice15
$ npm i -g lettokenburn-cli
$ ltb bench pull common-voice15

External harness. pip install crfm-helm && helm-run --run-entries common_voice_15:model=<model> --suite my-suite --max-eval-instances 100 (HELM scenario 'common_voice_15'; some scenarios need extra args) https://github.com/stanford-crfm/helm

License is link-only: ltb bench pull fetches rows from the original host for local evaluation only and does not write a solution/ directory. Do not redistribute the generated tasks.

Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs

Scores

0 sourced entries

No sourced scores recorded yet.

Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.

Reproduced by the community

All runs
Loading community runs…

About

CommonVoice15 Scenario

The most recent release of CommonVoice15 (Ardila et al, 2019) includes 114 languages. Over 50,000 individuals have participated so far, resulting in 2,500 hours of collected audio. This is the largest audio corpus in the public domain for speech recognition, both in terms of number of hours and number of languages. The task is to recognize the speech from the audio sample.

Paper: https://arxiv.org/abs/1912.06670 Code: https://github.com/common-voice/common-voice

Citation: @article{ardila2019common, title={Common voice: A massively-multilingual speech corpus}, author={Ardila, Rosana and Branson, Megan and Davis, Kelly and Henretty, Michael and Kohler, Michael and Meyer, Josh and Morais, Reuben and Saunders, Lindsay and Tyers, Francis M and Weber, Gregor}, journal={arXiv preprint arXiv:1912.06670}, year={2019} }