Quality Prediction For Generative Neural Speech Codecs (WARP-Q)

This code is to run the WARP-Q speech quality metric in a installable mode https://github.com/WissamJassim/WARP-Q.git

WARP-Q is an objective, full-reference metric for perceived speech quality. It uses a subsequence dynamic time warping (SDTW) algorithm as a similarity between a reference (original) and a test (degraded) speech signal to produce a raw quality score. It is designed to predict quality scores for speech signals processed by low bit rate speech coders.

Install

make requirements

Usage example

from warpq import warpq
from torch import randn
import torch

g = torch.manual_seed(1)
preds = randn(8000)
target = randn(8000)
print(warpq(preds, target, fs=16000))
(tensor(1.4610), tensor(4.2980))