Previously-obtained data, quantifying the degree of quality degradation resulting from a range of spatial audio processes (SAPs), can be used to build a regression model of perceived spatial audio quality in terms of previously developed spatially and timbrally relevant metrics. A generalizable model thus built, employing just five metrics and two principal components, performs well in its prediction of the quality of a range of program types degraded by a multitude of SAPs commonly encountered in consumer audio reproduction, auditioned at both central and off-center listening positions. Such a model can provide a correlation to listening test data of r = 0.89, with a root mean square error (RMSE) of 11%, making its performance comparable t...
International audienceSpatial audio technologies become very important in audio broadcast services. ...
The increased use of audio applications capable of conveying enhanced spatial quality puts focus on ...
The QESTRAL project has developed an artificial listener that compares the perceived quality of a sp...
Previously-obtained data, quantifying the degree of quality degradation resulting from a range of sp...
Spatial audio processes (SAPs) commonly encountered in consumer audio reproduction systems are known...
The QESTRAL (Quality Evaluation of Spatial Transmission and Reproduction using an Artificial Listene...
Spatial audio processes (SAPs) commonly encountered in consumer audio reproduction systems are known...
The research in this thesis describes the creation and development of a method for the prediction of...
The research in this thesis describes the creation and development of a method for the prediction of...
The QESTRAL project aims to develop an artificial listener for comparing the perceived quality of a ...
Most current perceptual models for audio quality have so far tended to concentrate on the audibility...
The increased use of audio applications capable of conveying enhanced spatial quality puts focus on ...
The spatial quality of automotive audio systems is often compromised due to their unideal listening ...
This paper describes a computational model for the prediction of perceived spatial quality for repro...
The spatial quality of audio content delivery systems is becoming increasingly important as service ...
International audienceSpatial audio technologies become very important in audio broadcast services. ...
The increased use of audio applications capable of conveying enhanced spatial quality puts focus on ...
The QESTRAL project has developed an artificial listener that compares the perceived quality of a sp...
Previously-obtained data, quantifying the degree of quality degradation resulting from a range of sp...
Spatial audio processes (SAPs) commonly encountered in consumer audio reproduction systems are known...
The QESTRAL (Quality Evaluation of Spatial Transmission and Reproduction using an Artificial Listene...
Spatial audio processes (SAPs) commonly encountered in consumer audio reproduction systems are known...
The research in this thesis describes the creation and development of a method for the prediction of...
The research in this thesis describes the creation and development of a method for the prediction of...
The QESTRAL project aims to develop an artificial listener for comparing the perceived quality of a ...
Most current perceptual models for audio quality have so far tended to concentrate on the audibility...
The increased use of audio applications capable of conveying enhanced spatial quality puts focus on ...
The spatial quality of automotive audio systems is often compromised due to their unideal listening ...
This paper describes a computational model for the prediction of perceived spatial quality for repro...
The spatial quality of audio content delivery systems is becoming increasingly important as service ...
International audienceSpatial audio technologies become very important in audio broadcast services. ...
The increased use of audio applications capable of conveying enhanced spatial quality puts focus on ...
The QESTRAL project has developed an artificial listener that compares the perceived quality of a sp...