Multilingual LibriSpeech
Models transcribe read audiobook speech in eight languages from LibriVox. Scored by word error rate.
Published at Interspeech 2020. Launch posts often report a subset of languages.
- Made by
- Meta AI (Pratap et al.)
- Released
- December 2020
- Kind
- Speech recognition and translation
- Level
- Everyday
- Scored
- Checked automatically
- Answers
- Open-ended
- Tasks
- All public
- Last in a launch post
- December 2025, dropped before it saturated
- Last model added
- December 2025
In the authors’ words
This paper introduces Multilingual LibriSpeech (MLS) dataset, a large multilingual corpus suitable for speech research. The dataset is derived from read audiobooks from LibriVox and consists of 8 languages, including about 44.5K hours of English and a total of about 6K hours for other languages. Additionally, we provide Language Models (LM) and baseline Automatic Speech Recognition (ASR) models and for all the languages in our dataset. We believe such a large transcribed dataset will open new avenues in ASR and Text-To-Speech (TTS) research. The dataset will be made freely available for anyone at http://www.openslr.org.
Nova 2 Omni Preview leads with 4.70
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.
- 1
Nova 2 Omni Preview 4.70
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 4.70 | Dec 2025 | Lab model card |
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 December 2025
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 |
|---|---|---|---|
| Dec 2, 2025 | 4.7 | MLS WER (English, Spanish, French, German, Italian) |
2 system cards report it, from 2 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 |
|---|---|---|---|---|
| Dec 2, 2025 | | 4.7 | MLS WER, English, Spanish, French, German and Italian, lower is better (Table 7) | Capabilities |
| Jul 17, 2025 | | MLS WER per language, lower is better: nl 9.43, fr 3.73, de 5.57, it 8.44, pt 5.85, es 3.62 (Table 6) | Capabilities |
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