Fact · Languages and accents
8.3percent word error rate
On the Fleurs benchmark, the Whisper large-v2 model had a word error rate of 8.3 percent for French.
Checked against its source on October 16, 2026
In the source's own words
“Model German Greek English Spanish Estonian Persian Finnish Tagalog French Galician Gujarati Hausa Hebrew Hindi ... Whisper large-v2 4.5 12.5 4.2 3.0 21.9 32.9 9.7 13.8 8.3 15.4 102.7 88.9 27.1 21.5”
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.
Source
Used to calculate
Cited on
- Dictation Languages, Accents and Voice TranslationTopic
- How Speech Recognition Works, From Sound to TextGuide
- Speech to Text With Translation on Phones and ComputersGuide
- Speech Recognition and Accents: Accuracy and FixesGuide
- Spanish Speech to Text and Talk to TextGuide
- Transcribe Audio With Whisper, ChatGPT or GeminiGuide
- Whisper Supported Languages and Accuracy by LanguageGuide
- Speech to Text in French, German, Russian and MoreGuide
- How do you dictate in French?Question