As binaural audio continues to permeate immersive technologies, it is vital to develop a detailed understanding of the perceptual relevance of HRTFs. Previous research has explored the benefit of individual HRTFs with respect to localisation. However, localisation is only one metric with which it is possible to rate spatial audio. This paper evaluates the perceived timbral and spatial characteristics of both individual and non-individual HRTFs and compares the results to overall preference. To that end, the measurement and evaluation of a high-resolution multi-environment binaural Impulse Response database is presented for 20 subjects, including the KU100 and KEMAR binaural mannequins. Post-processing techniques, including low frequency compensation and diffuse field equalisation are discussed in relation to the 8802 unique HRTFs measured for each mannequin and 2818/2114 HRTFs measured for each human. Listening test results indicate that particular HRTF sets are preferred more generally by subjects over their own individual measurements.

The classification of acoustic scenes and events is an emerging area of research in the field of machine listening. Most of the research conducted so far uses spectral features extracted from monaural or stereophonic audio rather than spatial features extracted from multichannel recordings. This is partly due to the lack thus far of a substantial body of spatial recordings of acoustic scenes. This paper formally introduces EigenScape, a new database of fourth-order Ambisonic recordings of eight different acoustic scene classes. The potential applications of a spatial machine listening system are discussed before detailed information on the recording process and dataset are provided. A baseline spatial classification system using directional audio coding (DirAC) techniques is detailed and results from this classifier are presented. The classifier is shown to give good overall scene classification accuracy across the dataset, with 7 of 8 scenes being classified with an accuracy of greater than 60% with an 11% improvement in overall accuracy compared to use of Mel-frequency cepstral coefficient (MFCC) features. Further analysis of the results shows potential improvements to the classifier. It is concluded that the results validate the new database and show that spatial features can characterise acoustic scenes and as such are worthy of further investigation.

The increasing popularity of Ambisonics as a spatial audio format for streaming services poses new challenges to existing audio coding techniques. Immersive audio delivered to mobile devices requires an efficient bitrate compression that does not affect the spatial quality of the content. Good localizability of virtual sound sources is one of the key elements that must be preserved. This study was conducted to investigate the localization precision of virtual sound source presentations within Ambisonic scenes encoded with Opus low-bitrate compression at different bitrates and Ambisonic orders (1st, 3rd, and 5th). The test stimuli were reproduced over a 50-channel spherical loudspeaker configuration and binaurally using individually measured and generic Head-Related Transfer Functions (HRTFs). Participants were asked to adjust the position of a virtual acoustic pointer to match the position of virtual sound source within the bitrate-compressed Ambisonic scene. Results show that auditory localization in low-bitrate compressed Ambisonic scenes is not significantly affected by codec parameters. The key factors influencing localization are the rendering method and Ambisonic order truncation. This suggests that efficient perceptual coding might be successfully used for mobile spatial audio delivery.

Ambisonics has enjoyed a recent resurgence in popularity due to virtual reality applications. Low order Ambisonic reproduction is inherently inaccurate at high frequencies, which causes poor timbre and height localisation. Diffuse-Field Equalisation (DFE), the theory of removing direction-independent frequency response, is applied to binaural (over headphones) Ambisonic rendering to address high-frequency reproduction. DFE of Ambisonics is evaluated by comparing binaural Ambisonic rendering to direct convolution via head-related impulse responses (HRIRs) in three ways: spectral difference, predicted sagittal plane localisation and perceptual listening tests on timbre. Results show DFE successfully improves frequency reproduction of binaural Ambisonic rendering for the majority of sound source locations, as well as the limitations of the technique, and set the basis for further research in the field.