# ASR-project/Multilingual-PR

<https://repo.masters-masters.com/en/repos/ASR-project/Multilingual-PR>

[Home](https://repo.masters-masters.com/en) › [ASR-project](https://repo.masters-masters.com/en/owners/ASR-project) › [Multilingual-PR](https://repo.masters-masters.com/en/repos/ASR-project/Multilingual-PR)

ASR-project/Multilingual-PR has 270 stars on GitHub. Its RepoMasters card: Alpha tier. Phoneme Recognition using pre-trained models Wav2vec2, HuBERT and…

| Field | Value |
| --- | --- |
| Owner | [ASR-project](https://repo.masters-masters.com/en/owners/ASR-project) |
| Stars | 270 |
| Forks | 24 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2022 |
| Topics | phone-recognition, asr, deep-learning, self-supervised-learning, speech-processing, speech-recognition, huggingface, huggingface-transformers, wandb, common-voice |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [ASR-project/Multilingual-PR](https://github.com/ASR-project/Multilingual-PR) |

## Repository

Phoneme Recognition using pre-trained models Wav2vec2, HuBERT and WavLM. Throughout this project, we compared specifically three different self-supervised models, Wav2vec (2019, 2020), HuBERT (2021) and WavLM (2022) pretrained on a corpus of English speech that we will use in various ways to perfor…

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.