模型:
Ubenwa/sb-ecapa-vggsound
This repository provides all the necessary tools to perform sound recognition with SpeechBrain using a model pretrained on VGGSound.
For a better experience, we encourage you to learn more about SpeechBrain .
The given model performance on the test set is:
Release | Error Rate (%) |
---|---|
28-02-23 | 42.8 |
author = {Brecht Desplanques and Jenthe Thienpondt and Kris Demuynck}, editor = {Helen Meng and Bo Xu and Thomas Fang Zheng}, title = {{ECAPA-TDNN:} Emphasized Channel Attention, Propagation and Aggregation in {TDNN} Based Speaker Verification}, booktitle = {Interspeech 2020}, pages = {3830--3834}, publisher = {{ISCA}}, year = {2020}, }Referencing VGGSound
title={Vggsound: A large-scale audio-visual dataset}, author={Chen, Honglie and Xie, Weidi and Vedaldi, Andrea and Zisserman, Andrew}, booktitle={ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, pages={721--725}, year={2020}, organization={IEEE} }
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} }