|
--- |
|
language: sk |
|
tags: |
|
- audio |
|
- automatic-speech-recognition |
|
- voxpopuli-v2 |
|
datasets: |
|
- voxpopuli |
|
license: cc-by-nc-4.0 |
|
inference: false |
|
--- |
|
|
|
# Wav2Vec2-base-VoxPopuli-V2 |
|
|
|
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained only in **sk** on **12.1k** unlabeled datat of the [VoxPopuli corpus](https://arxiv.org/abs/2101.00390). |
|
|
|
The model is pretrained on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. |
|
|
|
**Note**: This model does not have a tokenizer as it was pretrained on audio alone. In order to use this model for **speech recognition**, a tokenizer should be created and the model should be fine-tuned on labeled text data in **sk**. Check out [this blog](https://huggingface.co/blog/fine-tune-xlsr-wav2vec2) for a more in-detail explanation of how to fine-tune the model. |
|
|
|
**Paper**: *[VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation |
|
Learning, Semi-Supervised Learning and Interpretation](https://arxiv.org/abs/2101.00390)* |
|
|
|
**Authors**: *Changhan Wang, Morgane Riviere, Ann Lee, Anne Wu, Chaitanya Talnikar, Daniel Haziza, Mary Williamson, Juan Pino, Emmanuel Dupoux* from *Facebook AI*. |
|
|
|
See the official website for more information, [here](https://github.com/facebookresearch/voxpopuli/). |
|
|
