| --- |
| tags: |
| - speech |
| - speech-quality-assessment |
| - mos-prediction |
| - pytorch |
| --- |
| |
| # SSL Layer MOS checkpoints |
|
|
| This repository contains the projection-head checkpoints associated with |
| [SSL_Layer_MOS](https://github.com/Hope-Liang/SSL_Layer_MOS), the official |
| implementation for *Selection of Layers from Self-supervised Learning Models |
| for Predicting Mean-Opinion-Score of Speech* (IEEE ASRU 2025). |
|
|
| ## Contents |
|
|
| The checkpoints are grouped by evaluation dataset: |
|
|
| - `results_nisqa/` |
| - `results_tencent/` |
| - `results_bvcc/` |
|
|
| Within each dataset, files are organized by SSL model, layer, and run. Each |
| experiment includes PyTorch checkpoint files (`.pt`) and its Gin configuration |
| (`.gin`); logs are retained for reproducibility. |
|
|
| ## Usage |
|
|
| Clone the companion code repository and follow its inference instructions: |
|
|
| ```bash |
| git clone https://github.com/Hope-Liang/SSL_Layer_MOS.git |
| cd SSL_Layer_MOS |
| python inference.py --audio_path=<YOUR_AUDIO_PATH> --ssl_model=<SELECTED_SSL_MODEL> --ssl_layer=<SELECTED_SSL_LAYER> --ckpt=<PATH_TO_DOWNLOADED_CHECKPOINT> |
| ``` |
|
|
| Download a checkpoint from the directory matching your selected dataset, SSL |
| model, layer, and run. |
|
|
| ## Citation |
|
|
| If you use these checkpoints, please cite the associated IEEE ASRU 2025 paper |
| and the [companion implementation](https://github.com/Hope-Liang/SSL_Layer_MOS). |
|
|
| ## License |
|
|
| The license for these checkpoints follows the terms specified by the authors. |
| Please also comply with the licenses of any underlying SSL models and datasets. |
|
|
