ASR-project / Multilingual-PR

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 perform phoneme recognition for different languages with a network trained with Connectionist Temporal Classification (CTC) algorithm.

Date Created 2022-02-25 (2 years ago)

Commits 315 (last one 2 years ago)

Stargazers 217 (0 this week)

Watchers 6 (0 this week)

Forks 18

License unknown

Ranking

RepositoryStats indexes 610,149 repositories, of these ASR-project/Multilingual-PR is ranked #173,449 (72nd percentile) for total stargazers, and #302,145 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #30,961/123,095.

ASR-project/Multilingual-PR is also tagged with popular topics, for these it's ranked: deep-learning (#3,427/8643), speech-recognition (#241/541), huggingface (#133/398), asr (#94/222)

Other Information

ASR-project/Multilingual-PR has Github issues enabled, there are 2 open issues and 3 closed issues.

All Topics

asr wandb huggingface common-voice deep-learning phone-recognition speech-processing speech-recognition huggingface-transformers self-supervised-learning

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315 commits on the default branch (main) since jan '22

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updated: 2025-01-23 @ 02:29am, id: 463582488 / R_kgDOG6G1GA