Asteroid: The PyTorch-Based Audio Source Separation Toolkit for Researchers-Reference-Cited by-同舟云学术

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Asteroid: The PyTorch-Based Audio Source Separation Toolkit for Researchers

Published:2020-10-25 Issue: Volume: Page:
ISSN:
Container-title:Interspeech 2020
language:
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Author:

Pariente Manuel,Cornell Samuele,Cosentino Joris,Sivasankaran Sunit,Tzinis Efthymios,Heitkaemper Jens,Olvera Michel,Stöter Fabian-Robert,Hu Mathieu,Martín-Doñas Juan M.,Ditter David,Frank Ariel,Deleforge Antoine,Vincent Emmanuel

Publisher

ISCA

Cited by 96 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Audio-Visual Speech Separation Model Inspired by Cortico-Thalamo-Cortical Circuits;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-10

2. Analysis and interpretation of joint source separation and sound event detection in domestic environments;PLOS ONE;2024-07-05

3. Deep Learning–Based Denoising Improves Receiver Function Imaging Using Dense Short-Period Teleseismic Data;Seismological Research Letters;2024-07-03

4. Using deep learning to improve the intelligibility of a target speaker in noisy multi-talker environments for people with normal hearing and hearing loss;The Journal of the Acoustical Society of America;2024-07-01

5. End-to-end integration of speech separation and voice activity detection for low-latency diarization of telephone conversations;Speech Communication;2024-06

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