Fact · Languages and accents
17.5percent word error rate
On the Fleurs benchmark, the Whisper large-v2 model had a word error rate of 17.5 percent for Tamil.
Checked against its source on October 16, 2026
In the source's own words
“Model Swedish Swahili Tamil Telugu Tajik Thai Turkish Ukrainian Urdu Uzbek Vietnamese Yoruba ... Whisper large-v2 8.5 39.3 17.5 99.0 85.8 11.5 8.4 8.6 22.6 90.2 10.3 94.8”
Robust Speech Recognition via Large-Scale Weak Supervision (full text), Alec Radford et al., OpenAI (arXiv), 2022, Table 13 (Fleurs).
Open the original (DOI 10.48550/arXiv.2212.04356)- What it measures
- Fleurs is a read-speech benchmark in about 100 languages. The figure is the error rate of the largest Whisper model in the table, run without fine-tuning, in the paper's own evaluation.
- What it does not show
- Read speech in good audio. Real dictation, accents and noise raise error rates. For languages written without spaces the paper reports character-level scoring, and the error rate can exceed 100 percent when the model writes extra text.