Slawomir Zielinski

On the relative importance of spatial and timbral fidelities in judgments of degraded multichannel audio quality

Mean opinion score ratings of reproduced sound quality typically pool all contributing perceptual factors into a single rating of basic audio quality. In order to improve understanding of the trade-offs between selected sound quality degradations that might arise in systems for the delivery of high quality multichannel audio, it was necessary to evaluate the influence of timbral and spatial fidelity changes on basic audio quality grades. The relationship between listener ratings of degraded multichannel audio quality on one timbral and two spatial fidelity scales was exploited to predict basic audio quality ratings of the same material using a regression model. It was found that timbral fidelity ratings dominated but that spatial fidelity predicted a substantial proportion of the basic audio quality.

Relationships between experienced listener ratings of multichannel audio quality and naïve listener preferences.

The preferences of a large number of naïve listeners were elicited in response to a selection of multichannel audio items that had been degraded in quality by using band-limiting and down-mixing algorithms. Relationships were sought between these preference ratings and the quality judgements of experienced listeners in an attempt to determine whether one could be predicted from the other. Results suggest that a simple regression model can be used to do this with adequate results, but that a better prediction can be successfully based on experienced listener ratings of timbral and spatial fidelity. There is a difference between naïve and experienced listeners in the weightings of the fidelities and their relationship to overall quality.

Feature Extraction for the Prediction of Multichannel Spatial Audio Fidelity

This paper seeks to present an algorithm for the prediction of frontal spatial fidelity and surround spatial fidelity of multichannel audio, which are two attributes of the subjective parameter called basic audio quality. A number of features chosen to represent spectral and spatial changes were extracted from a set of recordings and used in a regression model as independent variables for the prediction of spatial fidelities. The calibration of the model was done by ridge regression using a database of scores obtained from a series of formal listening tests. The statistically significant features based on interaural cross correlation and spectral features found from an initial model were employed to build a simplified model and these selected features were validated. The results obtained from the validation experiment were highly correlated with the listening test scores and had a low standard error comparable to that encountered in typical listening tests. The applicability of the developed algorithm is limited to predicting the basic audio quality of low-pass filtered and down-mixed recordings (as obtained in listening tests based on a multistimulus test paradigm with reference and two anchors: a 3.5-kHz low-pass filtered signal and a mono signal)

Influence of visual cues on the perception of surround sound

Contemporary digital video, film, or multimedia presentations are often accompanied by the surround sound. Techniques and standards involved in digital video processing are much more developed than concepts underlying creating recording and mixing of the multichannel sound. The main challenge in the sound processing in the multichannel system is to create an appropriate basis for connecting multimodal context of visual and sound domains. Therefore one of the purposes of experiments is to study in which way and how the surround sound interferes or is associated with the visual context. This kind of study was hitherto carried out when two‐channel sound technique was associated with a stereo TV. However, there are not many studies done yet that associate surround sound and digital video presented at the TV screen. The main issue in such experiments is the analysis of the influence of visual cues on perception of the surround sound. This problem will be addressed in the paper.

Measuring perceived spatial quality changes in surround sound reproduction

The spatial quality of audio content delivery systems is becoming increasingly important as service providers attempt to deliver enhanced experiences of spatial immersion and naturalness in audio-visual applications. Examples are virtual reality, telepresence, home cinema, games and communications products. The QESTRAL project is developing an artificial listener that will compare the perceived quality of a spatial audio reproduction to a reference reproduction. The model is calibrated using data from listening tests, and utilises a range of metrics to predict the resulting spatial sound quality ratings. Potential application areas for the model are outlined, together with exemplary results obtained from some of its component parts.

Prediction of spatial perceptual attributes of reproduced sound across the listening area

Audio systems and recordings are optimized for listening at the “sweet spot,” but how well do they work elsewhere? An acoustic‐perceptual model has been developed that simulates sound reproduction in a variety of formats, including mono, two‐channel stereo, five‐channel surround and wavefield synthesis. A virtual listener placed anywhere in the listening area is used to extract binaural signals, and hence interaural cues to the spatial attributes of the soundfield. Using subjectively‐validated models of spatial sound perception, we can predict the way that human listeners would perceive these attributes, such as the direction (azimuth) and width of a phantom source. Results will be presented across the listening area for different source signals, sound scenes and reproduction systems, illustrating their spatial fidelity in perceptual terms. Future work investigates the effects of typical reproduction degradations.

A method for echo cancellation in audio signals using the genetic algorithm

A new method for echo cancellation is proposed. This method is based on inverse models of systems causing the echo in transmission channels. Parameters of these models are optimized using the genetic algorithm. In general, the inverse models that are used for echo cancellation can be divided into several categories according to their complexity. In the simplest case, the models consist of digital delay lines, scalers, and adders. The more complex models use also a nonlinear filtration, which in the general case may be a nonstationary one. The experiments and informal subjective listening tests showed that the proposed method allows for the perceptually efficient suppression of echo which was caused by multiple reflections providing delayed and scaled copies of the original signal. An additional preprocessing employing a calculation of the correlation function of the input signal can diminish the computational complexity of the proposed algorithm. Some examples of echo cancellation results obtained with th...