This repository provides all the necessary tools to perform enhancement with
SpeechBrain. For a better experience we encourage you to learn more about
SpeechBrain
. The model performance is:
Release
Test PESQ
Test STOI
21-04-27
3.15
93.0
Install SpeechBrain
First of all, please install SpeechBrain with the following command:
pip install speechbrain
Please notice that we encourage you to read our tutorials and learn more about
SpeechBrain
.
Pretrained Usage
To use the mimic-loss-trained model for enhancement, use the following simple code:
import torch
import torchaudio
from speechbrain.inference.enhancement import SpectralMaskEnhancement
enhance_model = SpectralMaskEnhancement.from_hparams(
source="speechbrain/metricgan-plus-voicebank",
savedir="pretrained_models/metricgan-plus-voicebank",
)
# Load and add fake batch dimension
noisy = enhance_model.load_audio(
"speechbrain/metricgan-plus-voicebank/example.wav"
).unsqueeze(0)
# Add relative length tensor
enhanced = enhance_model.enhance_batch(noisy, lengths=torch.tensor([1.]))
# Saving enhanced signal on disk
torchaudio.save('enhanced.wav', enhanced.cpu(), 16000)
The system is trained with recordings sampled at 16kHz (single channel).
The code will automatically normalize your audio (i.e., resampling + mono channel selection) when calling
enhance_file
if needed. Make sure your input tensor is compliant with the expected sampling rate if you use
enhance_batch
as in the example.
Inference on GPU
To perform inference on the GPU, add
run_opts={"device":"cuda"}
when calling the
from_hparams
method.
Training
The model was trained with SpeechBrain (d0accc8).
To train it from scratch follows these steps:
cd speechbrain
pip install -r requirements.txt
pip install -e .
Run Training:
cd recipes/Voicebank/enhance/MetricGAN
python train.py hparams/train.yaml --data_folder=your_data_folder
You can find our training results (models, logs, etc)
here
.
Limitations
The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
Referencing MetricGAN+
If you find MetricGAN+ useful, please cite:
@article{fu2021metricgan+,
title={MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement},
author={Fu, Szu-Wei and Yu, Cheng and Hsieh, Tsun-An and Plantinga, Peter and Ravanelli, Mirco and Lu, Xugang and Tsao, Yu},
journal={arXiv preprint arXiv:2104.03538},
year={2021}
}
Please, cite SpeechBrain if you use it for your research or business.
@misc{speechbrain,
title={{SpeechBrain}: A General-Purpose Speech Toolkit},
author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
year={2021},
eprint={2106.04624},
archivePrefix={arXiv},
primaryClass={eess.AS},
note={arXiv:2106.04624}
}
Runs of ethanpai speech on huggingface.co
7
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs
More Information About speech huggingface.co Model
speech huggingface.co is an AI model on huggingface.co that provides speech's model effect (), which can be used instantly with this ethanpai speech model. huggingface.co supports a free trial of the speech model, and also provides paid use of the speech. Support call speech model through api, including Node.js, Python, http.
speech huggingface.co is an online trial and call api platform, which integrates speech's modeling effects, including api services, and provides a free online trial of speech, you can try speech online for free by clicking the link below.
ethanpai speech online free url in huggingface.co:
speech is an open source model from GitHub that offers a free installation service, and any user can find speech on GitHub to install. At the same time, huggingface.co provides the effect of speech install, users can directly use speech installed effect in huggingface.co for debugging and trial. It also supports api for free installation.