Model card
Google USM.
Googleproprietary2B paramsConformer encoder + RNN-T/CTC
Universal Speech Model. Pretrained on 12M hours unlabeled + 28M hours supervised. 100+ languages.
§ 02 · Benchmarks
Every benchmark Google USM has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | LibriSpeech | Speech · Speech Recognition | wer-test-other | 4.1% | #6 | 2023-03-02 | source ↗ |
| 02 | LibriSpeech | Speech · Speech Recognition | wer-test-clean | 2.0% | #8 | 2023-03-02 | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 04 · Papers
1 paper with results for Google USM.
- 2023-03-02· Speech· 2 results
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages
§ 05 · Related models
Other Google models scored on Codesota.
§ 06 · Sources & freshness
Where these numbers come from.
arxiv
2
results
2 of 2 rows marked verified.