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espnet/Chenda_Li_wsj0_2mix_enh_train_enh_conv_tasnet_raw_valid.si_snr.ave
Chenda_Li_wsj0_2mix_enh_train_enh_conv_tasnet_raw_valid.si_snr.ave is a audio-to-audio model from espnet. Use it for the audio-to-audio task on the model card, and read the license before you ship it in a product. It is set up for espnet. The card lists the license as cc-by-4.0.
♻️ Imported from https://zenodo.org/record/4498562/
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From the Hugging Face model README
pip install espnet
espnet enhance noisy.wav -o enhanced.wav --model espnet/Chenda_Li_wsj0_2mix_enh_train_enh_conv_tasnet_raw_valid.si_snr.ave
import soundfile as sf
from espnet2.bin.enh_inference import SeparateSpeech
enh = SeparateSpeech.from_pretrained(model_tag="espnet/Chenda_Li_wsj0_2mix_enh_train_enh_conv_tasnet_raw_valid.si_snr.ave")
# channels are kept on the way in: a multi-channel model needs them
speech, rate = sf.read("noisy.wav", dtype="float32")
waves = enh(speech[None, ...], fs=rate)
# one wave per output stream, which is what tells the two tasks apart: an
# enhancement model returns one, a separation model one per speaker. This is
# what `espnet enhance` writes as enhanced.wav or enhanced.spk1.wav, ...
if len(waves) == 1:
sf.write("enhanced.wav", waves[0][0], rate)
else:
for i, wave in enumerate(waves, start=1):
sf.write(f"enhanced.spk{i}.wav", wave[0], rate)
Chenda_Li/wsj0_2mix_enh_train_enh_conv_tasnet_raw_valid.si_snr.ave♻️ Imported from https://zenodo.org/record/4498562/
This model was trained by Chenda Li using wsj0_2mix/enh1 recipe in espnet.
# coming soon
@inproceedings{watanabe2018espnet,
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
title={{ESPnet}: End-to-End Speech Processing Toolkit},
year={2018},
booktitle={Proceedings of Interspeech},
pages={2207--2211},
doi={10.21437/Interspeech.2018-1456},
url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={7654--7658},
year={2020},
organization={IEEE}
}
or arXiv:
@misc{watanabe2018espnet,
title={ESPnet: End-to-End Speech Processing Toolkit},
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
year={2018},
eprint={1804.00015},
archivePrefix={arXiv},
primaryClass={cs.CL}
}