Mittag G. Deep Learning Based Speech Quality Prediction 2022

Textbook in PDF format

This book presents how to apply recent machine learning (deep learning) methods for the task of speech quality prediction. The author shows how recent advancements in machine learning can be leveraged for the task of speech quality prediction and provides an in-depth analysis of the suitability of different deep learning architectures for this task. The author then shows how the resulting model outperforms traditional speech quality models and provides additional information about the cause of a quality impairment through the prediction of the speech quality dimensions of noisiness, coloration, discontinuity, and loudness.
Introduction
Quality Assessment of Transmitted Speech
Neural Network Architectures for Speech Quality Prediction
Double-Ended Speech Quality Prediction Using Siamese Networks
Prediction of Speech Quality Dimensions with Multi-Task Learning
Bias-Aware Loss for Training from Multiple Datasets
NISQA: A Single-Ended Speech Quality Model
Conclusions
A Dataset Condition Tables
B Train and Validation Dataset Dimension Histograms