Jon Francombe

Modeling listener distraction resulting from audio-on-audio interference

As devices that produce audio become more commonplace and increasingly portable, situations in which two competing audio programs are present occur more regularly. In order to support the design of systems intended to mitigate the effects of interfering audio (including sound field control, noise cancelation or source separation systems), it is desirable to model the perceived distraction in such situations. Distraction ratings were collected for a range of audio-on-audio interference situations including various target and interferer programs at three interferer levels, with and without road noise. Time-frequency target-to-interferer ratio (TIR) maps of the stimuli were created using a simple auditory model. A number of feature sets were extracted from the TIR maps, including combinations of mean, standard deviation, minimum and maximum TIR taken across the duration of the program item. In order to predict distraction ratings from the features, linear regression models were produced. The models were evaluated for goodness-of-fit (RMSE) and generalizability (using a K-fold cross-validation procedure). The best model performed well, with almost all predictions falling within the 95% confidence intervals of the perceptual data. A validation data set was used to test the model, suggesting areas for future improvement.

Perceptual Evaluation of Blind Source Separation in Object-Based Audio Production

Object-based audio has the potential to enable multimedia content to be tailored to individual listeners and their reproduction equipment. In general, object-based production assumes that the objects—the assets comprising the scene—are free of noise and interference. However, there are many applications in which signal separation could be useful to an object-based audio workflow, e.g., extracting individual objects from channel-based recordings or legacy content, or recording a sound scene with a single microphone array. This paper describes the application and evaluation of blind source separation (BSS) for sound recording in a hybrid channel-based and object-based workflow, in which BSS-estimated objects are mixed with the original stereo recording. A subjective experiment was conducted using simultaneously spoken speech recorded with omnidirectional microphones in a reverberant room. Listeners mixed a BSS-extracted speech object into the scene to make the quieter talker clearer, while retaining acceptable audio quality, compared to the raw stereo recording. Objective evaluations show that the relative short-term objective intelligibility and speech quality scores increase using BSS. Further objective evaluations are used to discuss the influence of the BSS method on the remixing scenario; the scenario shown by human listeners to be useful in object-based audio is the worst-case scenario among those tested.

Speech reaction time measurements for the evaluation of audio-visual spatial coherence

Perception of spatial coherence and boundaries for the fusion of spatially incoherent stimuli in the context of multimedia reproduction have mainly been studied with continuous judgment scales. As results vary greatly between different studies, reaction time measurements are proposed as an indirect measure of the perception of spatial incoherence. Word recognition tasks for spatially coherent and incoherent audio-visual stimuli were conducted. Results show that reaction time measurements are sensitive to audio-visual offsets and that they are affected at the smallest measured offset (5.1°).

Determining and labeling the preference dimensions of spatial audio replay

There are currently many spatial audio reproduction systems in domestic use (e.g. mono, stereo, surround sound, sound bars, and headphones). In an experiment, pairwise preference magnitude ratings for a range of such systems were collected from trained and untrained listeners. The ratings were analysed using internal preference mapping to: (i) uncover the principal perceptual dimensions of listener preference; (ii) label the dimensions based on important perceptual attributes; and (iii) observe differences between trained and untrained listeners. To aid with labelling the dimensions, perceptual attributes were elicited alongside the preference ratings and were analysed by: (i) considering a metric derived from the frequency of use of each attribute and the magnitude of the related preference judgements; and (ii) observing attribute use for comparisons between specific methods. The first preference dimension accounted for over 90% of the variance in ratings; all participants exhibited a preference for reproduction methods that were positively correlated with the first dimension (most notably 5-, 9-, and 22-channel surround sound). This dimension was related to multiple important attributes, including those associated with spatial capability and absence of distortions. The second dimension accounted for only a very small proportion of the variance, and appeared to separate the headphone method from the other methods. The trained and untrained listeners generally showed opposite preferences in the second dimension, suggesting that trained listeners have a higher preference for headphone reproduction than untrained listeners.