Vietnamese Self Supervised Learning Wav2Vec2 model Model We use wav2vec2 architecture for doing Self Supervised learning Data Our self supervised model is pre trained on a massive audio set of 13k hours of Vietnamese youtube audio, which includes: Clean audio Noise audio Conversation Multi gender and dialects Download We have already upload our pre trained model to the Huggingface. The base model trained 35 epochs and the large model trained 20 epochs in about 30 days using TPU V3 8. Based version ~ 95M params Large version ~ 317M params Usage Since our model has the same architecture as the English wav2vec2 version, you can use this notebook for more information on how to fine tune the model. Finetuned version VLSP 2020 ASR dataset Benchmark WER result on VLSP T1 testset: base model large model without LM 8.66 6.90 with 5 grams LM 6.53 5.32 Usage Acknowledgment We would like to thank the Google TPU Research Cloud (TRC) program and Soonson Kwon (Google ML Ecosystem programs Lead) for their support. Special thanks to my colleagues at VietAI and VAIS for their advice. Contact nguyenvulebinh@gmail.com / binh@vietai.org
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