ML-SUPERB
by Academic consortium (CMU + NTU + JHU + others)
Multilingual SUPERB — 143 languages × multiple tasks for self-supervised speech models.
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TL;DR
Best for probing multilingual self-supervised speech models (XLS-R, MMS, mHuBERT) across LID + ASR. Pricing: free.
Category
Open source
License
Apache-2.0
Stars
★ 2.6k
Last push
2026-03-12
Pricing
free
Platforms
GitHub, HuggingFace
What it is
ML-SUPERB is the multilingual extension of SUPERB — 143 languages across language identification and ASR tasks, designed for probing SSL speech encoders. Toolkit: Apache-2.0; component data licenses vary.
Best for: Probing multilingual self-supervised speech models (XLS-R, MMS, mHuBERT) across LID + ASR.
Watch out for: Apache-2.0 toolkit · underlying data licenses vary per corpus (Common Voice, MLS, Babel, etc.) · academic-only Babel subset. Cite: Shi et al., Interspeech 2023.
Watch out for: Apache-2.0 toolkit · underlying data licenses vary per corpus (Common Voice, MLS, Babel, etc.) · academic-only Babel subset. Cite: Shi et al., Interspeech 2023.
Install / use
git clone https://github.com/s3prl/s3prl # ML-SUPERB benchmark suiteFeatures
| Speaker diarization | No |
| Word-level timestamps | No |
| Streaming / real-time | No |
| Languages supported | 143 |
| HIPAA eligible | No |
Links
ML-SUPERB vs Whipscribe
| Feature | ML-SUPERB | Whipscribe |
|---|---|---|
| Category | Open source | Transcription APIs |
| Pricing | free | $4–$24 one-time packs (credits never expire) · $2 single unlock · 60 min free on signup |
| Speaker diarization | No | Yes |
| Word timestamps | No | Yes |
| Streaming | No | No |
| Languages | 143 | 99 |
| Platforms | GitHub, HuggingFace | Web, API, MCP |
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