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Computer Sciences, Acoustics, Communication engineering and systems
Delivering a 360-degree soundscape that matches full sphere visuals is an essential aspect of immersive VR. Ambisonics is a full sphere surround sound technique that takes into account the azimuth and elevation of sound sources, portraying source location above and below as well as around the horizontal plane of the listener. In contrast to channel-based methods, ambisonics representation offers the advantage of being independent of a specific loudspeaker set-up. Streaming ambisonics over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience (QoE). This work investigates the effect of audio channel compression via the OPUS 1.2 codec on the quality of spatial audio as perceived by listeners. In particular we evaluate the listening quality and localization accuracy of first-order ambisonic audio (FOA) and third-order ambisonic audio (HOA) compressed at various bitrates (i.e. 32, 64, 128 and 128, 256, 512kbps respectively). To assess the impact of OPUS compression on spatial audio a number of subjective listening tests were carried out. The sample set for the tests comprises both recorded and synthetic audio clips with a wide range of time-frequency characteristics. In order to evaluate localization accuracy of compressed audio a number of fixed and dynamic (moving vertically and horizontally) source positions were selected for the test samples. The results show that for compressed spatial audio, perceived quality and localization accuracy are influenced more by compression scheme, bitrate and ambisonic order than by sample content. The insights provided by this work into factors and parameters influencing QoE will guide future development of a objective spatial audio quality metric.
Narbutt, M. et al. (2017) Streaming VR for Immersion: Quality aspects of Compressed Spatial Audio. 23rd International Conference on Virtual Systems and Multimedia (VSMM2017), Dublin, Belfast, October 2017.