A randomised controlled trial of PEGASUS, a psychoeducational programme for young people with high-functioning autism spectrum disorder.

Psychoeducation is an essential component of postdiagnostic care for people with ASD (autism spectrum disorder), but there is currently no evidence base for clinical practice. We designed, manualised and evaluated PEGASUS (psychoeducation group for autism spectrum understanding and support), a group psychoeducational programme aiming to enhance the self-awareness of young people with ASD by teaching them about their diagnosis

The computational prediction of masking thresholds for ecologically valid interference scenarios

Auditory interference scenarios, where a listener wishes to attend to some target audio while being presented with interfering audio, are prevalent in daily life. The goal of developing an accurate computational model which can predict masking thresholds for such scenarios is still incomplete. While some sophisticated, physiologically inspired, masking prediction models exist, they are rarely tested with ecologically valid programmes (such as music and speech). In order to test the accuracy of model predictions human listener data were required. To that end a masking threshold experiment was conducted for a variety of target and interferer programmes. The results were analysed alongside predictions made by the computational auditory signal processing and prediction model of (Jepsen et al. 2008). Masking thresholds were predicted to within 3.6 dB root mean squared error with the greatest prediction inaccuracies occurring in the presence of speech. These results are comparable to those in (Glasberg and Moore 2005) for predicting the audibility of time-varying sounds in the presence of background sounds, which otherwise represent the most accurate predictions of this type in the literature. © 2013 Acoustical Society of America

Acoustic contrast, planarity and robustness of sound zone methods using a circular loudspeaker array

Since the mid 1990s, acoustics research has been undertaken relating to the sound zone problem—using loudspeakers to deliver a region of high sound pressure while simultaneously creating an area where the sound is suppressed—in order to facilitate independent listening within the same acoustic enclosure. The published solutions to the sound zone problem are derived from areas such as wave field synthesis and beamforming. However, the properties of such methods differ and performance tends to be compared against similar approaches. In this study, the suitability of energy focusing, energy cancelation, and synthesis approaches for sound zone reproduction is investigated. Anechoic simulations based on two zones surrounded by a circular array show each of the methods to have a characteristic performance, quantified in terms of acoustic contrast, array control effort and target sound field planarity. Regularization is shown to have a significant effect on the array effort and achieved acoustic contrast, particularly when mismatched conditions are considered between calculation of the source weights and their application to the system

The computational prediction of masking thresholds for ecologically valid interference scenarios

Auditory interference scenarios, where a listener wishes to attend to some target audio while being presented with interfering audio, are prevalent in daily life. The goal of developing an accurate computational model which can predict masking thresholds for such scenarios is still incomplete. While some sophisticated, physiologically inspired, masking prediction models exist, they are rarely tested with ecologically valid programmes (such as music and speech). In order to test the accuracy of model predictions human listener data were required. To that end a masking threshold experiment was conducted for a variety of target and interferer programmes. The results were analysed alongside predictions made by the computational auditory signal processing and prediction model of (Jepsen et al. 2008). Masking thresholds were predicted to within 3.6 dB root mean squared error with the greatest prediction inaccuracies occurring in the presence of speech. These results are comparable to those in (Glasberg and Moore 2005) for predicting the audibility of time-varying sounds in the presence of background sounds, which otherwise represent the most accurate predictions of this type in the literature. © 2013 Acoustical Society of America

The prediction of the acceptability of auditory interference based on audibility

In order to evaluate the ability of sound eld control methods to generate independent listening zones within domestic and automotive environments, it is useful to be able to predict, without listening tests, the accept- Ability of auditory interference scenarios. It was considered likely that a relationship would exist between masking thresholds and acceptability thresholds, thus a listening test was carried out to gather acceptability thresholds to compare with existing masking data collected under identical listening conditions. An analysis of the data revealed that a linear regression model could be used to predict acceptability thresholds, from only masking thresholds, with RMSE = 2.6 dB and R = 0.86. The same linear regression model was used to predict acceptability thresholds but with masking threshold predictions as the input. The results had RMSE = 4.2 dB and R = 0.88. Copyright © (2013) by the Audio Engineering Society

The acceptability of speech with interfering radio programme material

A listening test was conducted to investigate the acceptability of audio-on-audio interference for radio pro- grammes featuring speech as the target. 21 subjects, including na ̈ıve and expert listeners, were presented with 200 randomly assigned pairs of stimuli and asked to report, for each trial, whether the listening scenario was acceptable or unacceptable. Stimuli pairs were set to randomly selected SNRs ranging from 0 to 45 dB. Results showed no significant di↵erence between subjects according to listening experience. A logistic re- gression to acceptability was carried out based on SNR. The model had accuracy R2 = 0.87, RMSE = 14%,and RMSE* = 7%. By accounting for the presence of background audio in the target programme, 90% of the variance could be explained

The prediction of the acceptability of auditory interference based on audibility

In order to evaluate the ability of sound eld control methods to generate independent listening zones within domestic and automotive environments, it is useful to be able to predict, without listening tests, the accept- Ability of auditory interference scenarios. It was considered likely that a relationship would exist between masking thresholds and acceptability thresholds, thus a listening test was carried out to gather acceptability thresholds to compare with existing masking data collected under identical listening conditions. An analysis of the data revealed that a linear regression model could be used to predict acceptability thresholds, from only masking thresholds, with RMSE = 2.6 dB and R = 0.86. The same linear regression model was used to predict acceptability thresholds but with masking threshold predictions as the input. The results had RMSE = 4.2 dB and R = 0.88. Copyright © (2013) by the Audio Engineering Society

The acceptability of speech with interfering radio programme material

A listening test was conducted to investigate the acceptability of audio-on-audio interference for radio pro- grammes featuring speech as the target. 21 subjects, including na ̈ıve and expert listeners, were presented with 200 randomly assigned pairs of stimuli and asked to report, for each trial, whether the listening scenario was acceptable or unacceptable. Stimuli pairs were set to randomly selected SNRs ranging from 0 to 45 dB. Results showed no significant di↵erence between subjects according to listening experience. A logistic re- gression to acceptability was carried out based on SNR. The model had accuracy R2 = 0.87, RMSE = 14%,and RMSE* = 7%. By accounting for the presence of background audio in the target programme, 90% of the variance could be explained