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 (3 years ago)

Commits 315 (last one 2 years ago)

Stargazers 224 (0 this week)

Watchers 6 (0 this week)

Forks 19

License unknown

Ranking

RepositoryStats indexes 635,084 repositories, of these ASR-project/Multilingual-PR is ranked #173,991 (73rd percentile) for total stargazers, and #290,340 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #31,464/129,968.

ASR-project/Multilingual-PR is also tagged with popular topics, for these it's ranked: deep-learning (#3,415/8831), speech-recognition (#248/560), huggingface (#138/418), asr (#99/239)

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: 2025-03-30 @ 12:25pm, id: 463582488 / R_kgDOG6G1GA