
# Pre-trained checkpoints for speech representation in Japanese

The models in this repository were pre-trained via self-supervised learning (SSL) for speech representation.
The SSL models were built on the [fairseq](https://github.com/facebookresearch/fairseq) toolkit.

- `wav2vec2_base_csj.pt`
  - fairseq checkpoint of wav2vec2.0 model with *Base* architecture pre-trained on 16kHz sampled speech data of Corpus of Spontaneous Japanese (CSJ)
- `wav2vec2_base_csj_hf`
  - converted version of `wav2vec2_base_csj.pt` compatible with the interface of Hugging Face by using [this tool](https://github.com/huggingface/transformers/blob/main/src/transformers/models/wav2vec2/convert_wav2vec2_original_pytorch_checkpoint_to_pytorch.py)

If you find this helpful, please consider citing the following paper.

```text
@INPROCEEDINGS{ashihara_icassp23,
  author={Takanori Ashihara and Takafumi Moriya and Kohei Matsuura and Tomohiro Tanaka},
  title={Exploration of Language Dependency for Japanese Self-Supervised Speech Representation Models},
  booktitle={ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2023}
}
```

{"language": ["ja"], "license": "other", "library_name": "fairseq"}
fairseq ja license:other region:us
TAGS
#fairseq #ja #license-other #region-us 


# Pre-trained checkpoints for speech representation in Japanese

The models in this repository were pre-trained via self-supervised learning (SSL) for speech representation.
The SSL models were built on the fairseq toolkit.

- 'wav2vec2_base_csj.pt'
  - fairseq checkpoint of wav2vec2.0 model with *Base* architecture pre-trained on 16kHz sampled speech data of Corpus of Spontaneous Japanese (CSJ)
- 'wav2vec2_base_csj_hf'
  - converted version of 'wav2vec2_base_csj.pt' compatible with the interface of Hugging Face by using this tool

If you find this helpful, please consider citing the following paper.



# Pre-trained checkpoints for speech representation in Japanese

The models in this repository were pre-trained via self-supervised learning (SSL) for speech representation.
The SSL models were built on the fairseq toolkit.

- 'wav2vec2_base_csj.pt'
  - fairseq checkpoint of wav2vec2.0 model with *Base* architecture pre-trained on 16kHz sampled speech data of Corpus of Spontaneous Japanese (CSJ)
- 'wav2vec2_base_csj_hf'
  - converted version of 'wav2vec2_base_csj.pt' compatible with the interface of Hugging Face by using this tool

If you find this helpful, please consider citing the following paper.
TAGS
#fairseq #ja #license-other #region-us 
 # Pre-trained checkpoints for speech representation in Japanese

The models in this repository were pre-trained via self-supervised learning (SSL) for speech representation.
The SSL models were built on the fairseq toolkit.

- 'wav2vec2_base_csj.pt'
  - fairseq checkpoint of wav2vec2.0 model with *Base* architecture pre-trained on 16kHz sampled speech data of Corpus of Spontaneous Japanese (CSJ)
- 'wav2vec2_base_csj_hf'
  - converted version of 'wav2vec2_base_csj.pt' compatible with the interface of Hugging Face by using this tool

If you find this helpful, please consider citing the following paper.
TAGS
#fairseq #ja #license-other #region-us 
# Pre-trained checkpoints for speech representation in Japanese

The models in this repository were pre-trained via self-supervised learning (SSL) for speech representation.
The SSL models were built on the fairseq toolkit.

- 'wav2vec2_base_csj.pt'
  - fairseq checkpoint of wav2vec2.0 model with *Base* architecture pre-trained on 16kHz sampled speech data of Corpus of Spontaneous Japanese (CSJ)
- 'wav2vec2_base_csj_hf'
  - converted version of 'wav2vec2_base_csj.pt' compatible with the interface of Hugging Face by using this tool

If you find this helpful, please consider citing the following paper.