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This package is written for MOS score prediction based on fine-tuned wav2vec2.0 model

Project description

WV-MOS

MOS score prediction by fine-tuned wav2vec2.0 model

Keywords: MOS-Net, MB-Net, PESQ, STOI, speech quality

Getting started

The package installation was tested with python3.9

pip install git+https://github.com/AndreevP/wvmos

Inference

from wvmos import get_wvmos
model = get_wvmos(cuda=True)

mos = model.calculate_one("path/to/wav/file") # infer MOS score for one audio 

mos = model.calculate_dir("path/to/dir/with/wav/files", mean=True) # infer average MOS score across .wav files in directory

Citation and Acknowledgment

This work was done for the deep learning course in Skolteh university by Pavel Andreev, Nikolay Patakin, Oleg Desheulin, Alexander Kagan and Arthur Bulanbaev. More details are described in paper https://arxiv.org/abs/2203.13086

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1.0

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