README.md

metadata

language: vi
datasets:
  - youtube-vi-13k-hours
tags:
  - speech
license: cc-by-nc-4.0

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.

• Based version ~ 95M params
• Large version ~ 317M params

Usage

from transformers import Wav2Vec2ForPreTraining, Wav2Vec2Processor

model_name = 'nguyenvulebinh/wav2vec2-base-vi'
# model_name = 'nguyenvulebinh/wav2vec2-large-vi'

model = Wav2Vec2ForPreTraining.from_pretrained(model_name)
processor = Wav2Vec2Processor.from_pretrained(model_name)

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.

Contact

[email protected] / [email protected]