Add pretrained weights from Voxpopuli
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 2.9k
- Forks
- 799
- Avg merge
- 58m
- Merged PRs (30d)
- 3
Description
VoxPopuli publishes pre-trained models of many different languages under CC BY-NC 4.0 license. We can add them to torchaudio.
non-fine-tuned weights
https://github.com/facebookresearch/voxpopuli#wav2vec-20
- es - base
- es - large
- fr - base
- fr - large
- it - base
- it - large
- ni - base
- ni - large
- sv - base
- sv - large
- 23 langs (10k subset) - base
- 23 langs (10k subset) - large
- 23 langs (100k subset) - base
- 23 langs (100k subset) - large
Fine-tuned ASR
https://github.com/facebookresearch/voxpopuli#asr-and-lm
- cs
- de #1953
- en #1956
- es #1924
- et
- fi
- fr #1919
- hr
- hu
- it #1954
- lt
- ni
- pl
- ro
- sk
- sl
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the VoxPopuli wav2vec 2.0 and ASR/LM links in the issue, then review how torchaudio currently exposes pretrained models. The checklist is the completion target: add the remaining non-fine-tuned and fine-tuned language weights, while accounting for the already referenced issues #1919, #1924, #1953, and #1954.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100