Common Voice
Nova 2.0 Pro Preview 5.50% leads since December 2025 Crowd-sourced multilingual read-speech corpus. Used here as an ASR test set scored by word error rate.
Mozilla releases numbered corpus versions such as 13.0 and 17.0, so reports should name the version. Since 2025-10 the datasets are only on Mozilla Data Collective, not Hugging Face.
- Made by
- Mozilla
- Released
- December 2019
- Kind
- Speech recognition and translation
- Level
- Everyday
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Last in a launch post
- July 2026, dropped before it saturated
- Last model added
- July 2026
In the authors’ words
The Common Voice corpus is a massively-multilingual collection of transcribed speech intended for speech technology research and development. Common Voice is designed for Automatic Speech Recognition purposes but can be useful in other domains (e.g. language identification). To achieve scale and sustainability, the Common Voice project employs crowdsourcing for both data collection and data validation. The most recent release includes 29 languages, and as of November 2019 there are a total of 38 languages collecting data. Over 50,000 individuals have participated so far, resulting in 2,500 hours of collected audio. To our knowledge this is the largest audio corpus in the public domain for speech recognition, both in terms of number of hours and number of languages. As an example use case for Common Voice, we present speech recognition experiments using Mozilla's DeepSpeech Speech-to-Text toolkit. By applying transfer learning from a source English model, we find an average Character Error Rate improvement of 5.99 +/- 5.48 for twelve target languages (German, French, Italian, Turkish, Catalan, Slovenian, Welsh, Irish, Breton, Tatar, Chuvash, and Kabyle). For most of these languages, these are the first ever published results on end-to-end Automatic Speech Recognition.
Nova 2.0 Pro Preview leads with 5.50% among models released by July 2026
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
The newest model with a score here came out in July 2026, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon - GPT-6 Astra
- Claude Opus 5.5
- and 16 more
- 1 Nova 2.0 Pro Preview 5.50%
- 2 Nova 2 Omni Preview 5.70%
- 3
Phi-4-multimodal 6.80% - 4
Qwen3-ASR-1.7B 9.18% - 5 GPT-Live-Transcribe 19.7%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Nova 2.0 Pro Preview | 5.50% | Dec 2025 | Lab model card | |
| 2 | Nova 2 Omni Preview | 5.70% | Dec 2025 | Lab model card | |
| 3 | Phi-4-multimodal | 6.80% | Mar 2025 | Lab model card | |
| 4 | Qwen3-ASR-1.7B | 9.18% | Jan 2026 | Lab model card | |
| 5 | GPT-Live-Transcribe | 19.7% | Jul 2026 | Lab model card |
2 models have held number one in labs’ own numbers since 2023
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs headline it less often now, last in July 2026
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Jul 29, 2026 | GPT-Live-Transcribe | 19.7 | Common Voice transcription error rate across 22 languages |
| Mar 30, 2026 | Qwen3.5-Omni-Plus | 3.13 | Mean of CV15 zh 3.46 / yue 1.95 / zh-tw 2.27 / en 4.83 |
| Jan 29, 2026 | Qwen3-ASR-1.7B | 9.18 | CommonVoice multilingual WER, Qwen3-ASR-1.7B, 13 languages |
| Dec 2, 2025 | Nova 2 Omni Preview | 5.7 | Common Voice (v15) WER, five languages |
| Dec 2, 2025 | Nova 2.0 Pro Preview | 5.5 | Common Voice WER, EFIGS average |
| Oct 31, 2025 |  LongCat-Flash-Omni | 4.98 | CommonVoice 15 (zh | en) 4.98 | 13.59 |
| Sep 22, 2025 | Qwen3-Omni-30B-A3B | 5.18 | Mean of CV15-en 6.05 / CV15-zh 4.31 |
| Jul 15, 2025 |  Voxtral Small | Mozilla Common Voice, macro-average WER (chart) | |
| Mar 27, 2025 | Qwen2.5-Omni-7B | 6.9 | Mean of Common Voice 15 en 7.6 / zh 5.2 / yue 7.3 / fr 7.5 |
8 system cards report it, from 5 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Apr 17, 2026 | Qwen3.5-Omni-Plus technical report | CV15 ASR WER zh 3.46, yue 1.95, zh-tw 2.27, en 4.83, no overall (Table 5) | Capabilities | |
| Dec 2, 2025 | Nova 2 Omni Preview technical report | 5.7 | Common Voice (v15) WER, five languages, lower is better (Table 7) | Capabilities |
| Dec 2, 2025 | Nova 2.0 Pro Preview technical report | 5.5 | Common Voice WER, EFIGS average, lower is better (Table 3) | Capabilities |
| Oct 31, 2025 | LongCat-Flash-Omni technical report | CommonVoice 15 zh 4.98, en 13.59, error rate, lower is better, no overall score (Table 9) | Capabilities | |
| Sep 22, 2025 | Qwen3-Omni-30B-A3B technical report | CV15-en 6.05, CV15-zh 4.31, WER, lower is better, Instruct, no overall score (Table 6) | Capabilities | |
| Jul 17, 2025 | Voxtral Small technical report | Mozilla Common Voice 15.1 WER per language with no printed macro-average, lower is better: ar 61.97, nl 3.98, en 8.58, fr 6.18, de 3.74, hi 9.01, it 3.96, pt 6.43, es 3.31 (Table 5, Figure 3 chart) | Capabilities | |
| Mar 26, 2025 | Qwen2.5-Omni-7B technical report | Common Voice 15 en 7.6, zh 5.2, yue 7.3, fr 7.5, WER, lower is better, no overall score (Table 2) | Capabilities | |
| Mar 3, 2025 | Phi-4-multimodal technical report | 6.8 | CV15 (CommonVoice 15) ASR, WER average over 8 languages, lower is better (Tables 3 and 4) | Capabilities |
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