| | --- |
| | license: apache-2.0 |
| | datasets: |
| | - librispeech_asr |
| | language: |
| | - en |
| | library_name: sklearn |
| | --- |
| | |
| | <iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=medium" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe> |
| | <br/><br/> |
| |
|
| | # K-means (Quantization) |
| | This folder contains pre-trained K-means models for the LibriSpeech Dataset. |
| | The model serves to quantize self-supervised representations into discrete representation. Thus representations can be used as a discrete audio input for various tasks including classification, ASR and speech gneration. |
| | It supports kmeans models using the features from HuBERT, WAVLM or Wav2Vec. |
| |
|
| | ### Training |
| | The model was trained with SpeechBrain. |
| | To train it from scratch follow these steps: |
| | 1. Clone SpeechBrain: |
| | ```bash |
| | git clone --branch unstable-v0.6 https://github.com/speechbrain/speechbrain/ |
| | ``` |
| | 2. Install it: |
| | ```bash |
| | cd speechbrain |
| | pip install -r requirements.txt |
| | pip install -e . |
| | ``` |
| |
|
| | 3. Run Training: |
| | ```bash |
| | cd recipes/LibriSpeech/quantization/ |
| | pip install -r rextra-requirements.txt |
| | python train.py hparams/train_with_[ssl_model].yaml --data_folder=your_data_folder |
| | ``` |
| |
|
| | You can find our training results (models, logs, etc) [here](https://huggingface.co/speechbrain/SSL_Quantization). |
| |
|
| | ### Limitations |
| | The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets. |
| |
|
| | #### Referencing SpeechBrain |
| |
|
| | ``` |
| | @misc{SB2021, |
| | author = {Ravanelli, Mirco and Parcollet, Titouan and Rouhe, Aku and Plantinga, Peter and Rastorgueva, Elena and Lugosch, Loren and Dawalatabad, Nauman and Ju-Chieh, Chou and Heba, Abdel and Grondin, Francois and Aris, William and Liao, Chien-Feng and Cornell, Samuele and Yeh, Sung-Lin and Na, Hwidong and Gao, Yan and Fu, Szu-Wei and Subakan, Cem and De Mori, Renato and Bengio, Yoshua }, |
| | title = {SpeechBrain}, |
| | year = {2021}, |
| | publisher = {GitHub}, |
| | journal = {GitHub repository}, |
| | howpublished = {\\\\url{https://github.com/speechbrain/speechbrain}}, |
| | } |
| | ``` |
| |
|
| | #### About SpeechBrain |
| | SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-of-the-art performance is obtained in various domains. |
| |
|
| | Website: https://speechbrain.github.io/ |
| |
|
| | GitHub: https://github.com/speechbrain/speechbrain |
