Error activity and error entropy as a measure of psychoacoustic significance in the perceptual domain

Hollier, M. P.; Hawksford, Malcolm O. J.; Guard, David R.

doi:10.1049/ip-vis:19941248

Cited by 35 publications

(9 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This work has led to considerable progress in developing objective models of human quality perception for both audio [1], [2] and video [3], [4]. The development of unimodal perceptual models offer the telecommunication industry with valuable test and measurement tools, removing the need to perform costly and time-consuming subjective tests.…”

Section: Introductionmentioning

confidence: 99%

A Basic Multimedia Quality Model

Hands

2004

IEEE Trans. Multimedia

142

View full text Add to dashboard Cite

This paper describes two experiments designed to develop a basic multimedia predictive quality metric. In Experiment 1, two head and shoulder audio-video sequences were used for test material. Experiment 2 used one of the head and shoulder sequences from Experiment 1 together with a different, high-motion sequence. In both experiments, subjects assessed the audio quality first, followed by the video quality and finally a third test evaluated multimedia quality. The results of these studies found that human subjects integrate audio and video quality together using a multiplicative rule. A regression analysis using the subjective quality test data from each experiment found that: 1) for head and shoulder content, both modalities contribute significantly to the predictive power of the resultant model, although audio quality is weighted slightly higher than video quality and 2) for high-motion content, video quality is weighted significantly higher than audio quality.Index Terms-Multimedia, objective measurement, perceptual quality.

show abstract

Section: Introductionmentioning

confidence: 99%

A Basic Multimedia Quality Model

Hands

2004

IEEE Trans. Multimedia

142

View full text Add to dashboard Cite

show abstract

“…A major difference among algorithms of this kind is in the postprocessing of the auditory error surface. Hollier et al [17] uses an entropy measure of the error surface. MNB uses a hierarchical structure of integration over a range of time and frequency intervals.…”

Section: Current Objective Methodsmentioning

confidence: 99%

Objective Speech Quality Measurement Using Statistical Data Mining

Zha

Chan

2005

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

Measuring speech quality by machines overcomes two major drawbacks of subjective listening tests, their low speed and high cost. Real-time, accurate, and economical objective measurement of speech quality opens up a wide range of applications that cannot be supported with subjective listening tests. In this paper, we propose a statistical data mining approach to design objective speech quality measurement algorithms. A large pool of perceptual distortion features is extracted from the speech signal. We examine using classification and regression trees (CART) and multivariate adaptive regression splines (MARS), separately and jointly, to select the most salient features from the pool, and to construct good estimators of subjective listening quality based on the selected features. We show designs that use perceptually significant features and outperform the state-of-the-art objective measurement algorithm. The designed algorithms are computationally simple, making them suitable for real-time implementation. The proposed design method is scalable with the amount of learning data; thus, performance can be improved with more offline or online training

show abstract

“…According to the cognitive modeling literature, localized errors dominate the perception of audio quality [10], i.e. a highly concentrated error in time and frequency is found to have a greater subjective impact than a distributed error.…”

Section: ) Cognitive Modeling: Localized Versus Distributed Errorsmentioning

confidence: 99%

A technical framework for automatic perceptual evaluation of singing quality

Gupta

Wang

2018

SIP

View full text Add to dashboard Cite

Human experts evaluate singing quality based on many perceptual parameters such as intonation, rhythm, and vibrato, with reference to music theory. We proposed previously the Perceptual Evaluation of Singing Quality (PESnQ) framework that incorporated acoustic features related to these perceptual parameters in combination with the cognitive modeling concept of the telecommunication standard Perceptual Evaluation of Speech Quality to evaluate singing quality. In this study, we present further the study of the PESnQ framework to approximate the human judgments. First, we find that a linear combination of the individual perceptual parameter human scores can predict their overall singing quality judgment. This provides us with a human parametric judgment equation. Next, the prediction of the individual perceptual parameter scores from the PESnQ acoustic features show a high correlation with the respective human scores, which means more meaningful feedback to learners. Finally, we compare the performance of early fusion and late fusion of the acoustic features in predicting the overall human scores. We find that the late fusion method is superior to that of the early fusion method. This work underlines the importance of modeling human perception in automatic singing quality assessment.

show abstract

Error activity and error entropy as a measure of psychoacoustic significance in the perceptual domain

Cited by 35 publications

References 0 publications

A Basic Multimedia Quality Model

A Basic Multimedia Quality Model

Objective Speech Quality Measurement Using Statistical Data Mining

A technical framework for automatic perceptual evaluation of singing quality

Contact Info

Product

Resources

About