AES San Francisco 2008
Paper Session P16
Saturday, October 4, 10:30 am — 1:00 pmP16 - Spatial Audio Quality with Playback Demonstration on Sunday 9:00 am – 10:00 am
Chair: Francis Rumsey, University of Surrey - Guildford, Surrey, UK
P16-1 QESTRAL (Part 1): Quality Evaluation of Spatial Transmission and Reproduction Using an Artificial Listener—Francis Rumsey, Slawomir Zielinski, Philip Jackson, Martin Dewhirst, Robert Conetta, Sunish George, University of Surrey - Guildford, Surrey, UK; Søren Beck, Bang & Olufsen a/s - Struer, Denmark; David Meares, DJM Consultancy - Sussex, UK
Most current perceptual models for audio quality have so far tended to concentrate on the audibility of distortions and noises that mainly affect the timbre of reproduced sound. The QESTRAL model, however, is specifically designed to take account of distortions in the spatial domain such as changes in source location, width, and envelopment. It is not aimed only at codec quality evaluation but at a wider range of spatial distortions that can arise in audio processing and reproduction systems. The model has been calibrated against a large database of listening tests designed to evaluate typical audio processes, comparing spatially degraded multichannel audio material against a reference. Using a range of relevant metrics and a sophisticated multivariate regression model, results are obtained that closely match those obtained in listening tests.
Convention Paper 7595 (Purchase now)
P16-2 QESTRAL (Part 2): Calibrating the QESTRAL Model Using Listening Test Data—Robert Conetta, Francis Rumsey, Slawomir Zielinski, Phillip Jackson, Martin Dewhirst, University of Surrey - Guildford, Surrey, UK; Søren Beck, Bang & Olufsen a/s - Struer, Denmark; David Meares, DJM Consultancy - Sussex, UK; Sunish George, University of Surrey - Guildford, Surrey, UK
The QESTRAL model is a perceptual model that aims to predict changes to spatial quality of service between a reference system and an impaired version of the reference system. To achieve this, the model required calibration using perceptual data from human listeners. This paper describes the development, implementation, and outcomes of a series of listening experiments designed to investigate the spatial quality impairment of 40 processes. Assessments were made using a multi-stimulus test paradigm with a label-free scale, where only the scale polarity is indicated. The tests were performed at two listening positions, using experienced listeners. Results from these calibration experiments are presented. A preliminary study on the process of selecting of stimuli is also discussed.
Convention Paper 7596 (Purchase now)
P16-3 QESTRAL (Part 3): System and Metrics for Spatial Quality Prediction—Philip J. B. Jackson, Martin Dewhirst, Rob Conetta, Slawomir Zielinski, Francis Rumsey, University of Surrey - Guildford, Surrey, UK; David Meares, DJM Consultancy - Sussex, UK; Søren Bech, Bang & Olufsen A/S - Struer, Denmark; Sunish George, University of Surrey - Guildford, Surrey, UK
The QESTRAL project aims to develop an artificial listener for comparing the perceived quality of a spatial audio reproduction against a reference reproduction. This paper presents implementation details for simulating the acoustics of the listening environment and the listener's auditory processing. Acoustical modeling is used to calculate binaural signals and simulated microphone signals at the listening position, from which a number of metrics corresponding to different perceived spatial aspects of the reproduced sound field are calculated. These metrics are designed to describe attributes associated with location, width, and envelopment attributes of a spatial sound scene. Each provides a measure of the perceived spatial quality of the impaired reproduction compared to the reference reproduction. As validation, individual metrics from listening test signals are shown to match closely subjective results obtained, and can be used to predict spatial quality for arbitrary signals.
Convention Paper 7597 (Purchase now)
P16-4 QESTRAL (Part 4): Test Signals, Combining Metrics and the Prediction of Overall Spatial Quality—Martin Dewhirst, Robert Conetta, Francis Rumsey, Philip Jackson, Slawomir Zielinski, Sunish George, University of Surrey - Guildford, Surrey, UK; Søren Beck, Bang & Olufsen A/S - Struer, Denmark; David Meares, DJM Consultancy - Sussex, UK
The QESTRAL project has developed an artificial listener that compares the perceived quality of a spatial audio reproduction to a reference reproduction. Test signals designed to identify distortions in both the foreground and background audio streams are created for both the reference and the impaired reproduction systems. Metrics are calculated from these test signals and are then combined using a regression model to give a measure of the overall perceived spatial quality of the impaired reproduction compared to the reference reproduction. The results of the model are shown to match closely the results obtained in listening tests. Consequently, the model can be used as an alternative to listening tests when evaluating the perceived spatial quality of a given reproduction system, thus saving time and expense.
Convention Paper 7598 (Purchase now)
P16-5 An Unintrusive Objective Model for Predicting the Sensation of Envelopment Arising from Surround Sound Recordings—Sunish George, Slawomir Zielinski, Francis Rumsey, Robert Conetta, Martin Dewhirst, Philip Jackson, University of Surrey - Guildford, Surrey, UK; David Meares, DJM Consultancy - West Sussex, UK; Søren Bech, Bang & Olufsen A/S - Struer, Denmark
This paper describes the development of an unintrusive objective model, developed independently as a part of QESTRAL project, for predicting the sensation of envelopment arising from commercially available 5-channel surround sound recordings. The model was calibrated using subjective scores obtained from listening tests that used a grading scale defined by audible anchors. For predicting subjective scores, a number of features based on Inter-Aural Cross Correlation (IACC), Karhunen-Loeve Transform (KLT), and signal energy levels were extracted from recordings. The ridge regression technique was used to build the objective model, and a calibrated model was validated using a listening test scores database obtained from a different group of listeners, stimuli, and location. The initial results showed a high correlation between predicted and actual scores obtained from listening tests.
Convention Paper 7599 (Purchase now)