mattiadg / fairseq-automos

Automatic MOS prediction using Wav2Vec2 from Fairseq published as baseline for the VoiceMOS Challenge 2022 published by the National Institute of Informatics

This is code adapted from the baseline model for the VoiceMOS 2022 challenge to be used for convenient MOS prediction on arbitrary audio data.

For the original code please refer to: https://github.com/nii-yamagishilab/mos-finetune-ssl, which is provided by the National Institute of Informatics, Japan.

The audio normalization scripts are taken from: https://zenodo.org/record/6572573

Please cite the original publication when using this code:

"Generalization Ability of MOS Prediction Networks" Erica Cooper, Wen-Chin Huang, Tomoki Toda, Junichi Yamagishi https://ieeexplore.ieee.org/document/9746395 (published at ICASSP 2022)

Installation:

• Please install the Python packages: numpy, scipy, torch, torchaudio, fairseq
• Use install_sv56.sh to download and compile the sv56 tool from the ITU-T SLT
• Use download_w2v_small.sh to download the pretrained models

License

BSD 3-Clause License

Copyright (c) 2021, Yamagishi Laboratory, National Institute of Informatics All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

• Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

• Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

• Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.