Integral And Diagnostic Intrusive Prediction Of Speech Quality
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Integral and Diagnostic Intrusive Prediction of Speech Quality
Author: Nicolas Côté
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-05-06
This work deals with the instrumental measurement methods for the perceived quality of transmitted speech. These measures simulate the speech perception process employed by human subjects during auditory experiments. The measure standardized by the International Telecommunication Union (ITU), called “Wideband-Perceptual Speech Quality Evaluation (WB-PESQ)”, is not able to quantify all these perceived characteristics on a unidimensional quality scale, the Mean Opinion Score (MOS) scale. Recent experimental studies showed that subjects make use of several perceptual dimensions to judge about the quality of speech signals. In order to represent the signal at a higher stage of perception, a new model, called “Diagnostic Instrumental Assessment of Listening quality (DIAL)”, has been developed. It includes a perceptual and a cognitive model which simulate the whole quality judgment process. Except for strong discontinuities, DIAL predicts very well speech quality of different speech processing and transmission systems, and it outperforms the WB-PESQ.
Deep Learning Based Speech Quality Prediction
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.
Audiovisual Quality Assessment and Prediction for Videotelephony
The work presented in this book focuses on modeling audiovisual quality as perceived by the users of IP-based solutions for video communication like videotelephony. It also extends the current framework for the parametric prediction of audiovisual call quality. The book addresses several aspects related to the quality perception of entire video calls, namely, the quality estimation of the single audio and video modalities in an interactive context, the audiovisual quality integration of these modalities and the temporal pooling of short sample-based quality scores to account for the perceptual quality impact of time-varying degradations.