Codesota · Audio · Automatic Speech Recognition · FleursTasks/Audio/Automatic Speech Recognition
Automatic Speech Recognition · benchmark dataset · EN

Fleurs.

The Fleurs dataset is used for automatic speech recognition and speech classification. It is an n-way parallel speech dataset in 102 languages built on top of the FLoRes-101 benchmark, with approximately 12 hours of speech supervision per language. It covers 10 languages native to Southeast Asia and 3 other major languages (Mandarin Chinese, Portuguese, and Tamil) mostly spoken in a few Southeast Asian countries.

Paper Submit a result
§ 01 · Leaderboard

Best published scores.

No results indexed yet — be the first to submit a score.

No benchmark results indexed yet
§ 06 · Contribute

Have a score that beats
this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

Submit a result Read submission guide
What a submission needs
  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies