# AMBIQUAL: Towards a Quality Metric for Headphone Rendered Compressed Ambisonic Spatial Audio
## 1 Introduction  
To create an immersive virtual reality experience both graphics and spatial audio need to be of high quality and synchronized to the user's head movements in real time. In addition, audio sources must be accurately positioned such that they are localized at the correct azimuth and elevation. The most popular spatial audio format, known as Ambisonics B-format, was developed in the 1970s [1] and has been adopted by Google as the preferred audio format for Google VR and YouTube [2]. Facebook alsoimplements Ambisonics in the Oculus headset. In contrast to existing channel-based methods such as stereo, 5.1, or 7.1 surround sound, Ambisonics B-format does not encode loudspeaker information. Instead it encodes the whole spherical soundfield around the listener's head using spherical harmonics. A key advantage is that it is independent of any specific loudspeaker configuration. Ambisonics audio may be decoded to any loudspeaker layout and any number of loudspeakers, including a pair of headphones which will be the focus of our study. Efficient encoding techniques are required for spatial audio streaming over networks. Such techniques should be capable of compressing audio content without affecting quality of experience. Objective audio quality metrics to predict quality and spatial localization accuracy of compressed spatial audio are required by many streaming services. Our work focuses on compressed spatial audio delivery for YouTube 360 videos which are typically consumed on VR headsets in which audio is delivered over headphones. As such, the experiments presented do not deal with Ambisonic audio delivered over loudspeakers. Spatial audio is a broad and active research topic. Capturing, storing, transporting and delivering high-fidelity spatial audio poses many challenges that are out of scope for this work. This paper presents AMBIQUAL, a full reference objective audio quality metric designed to estimate the robustness of Ambisonic audio to compression in terms of perceived quality and localization accuracy. More specifically, we compare AMBIQUAL quality predictions with subjective quality assessments across a variety of natural and synthetic audio samples which have been compressed using the Opus 1.2 codec at various bit rates. We focus on the Opus 1.2 codec in this paper given its prevalent use in YouTube but the methodology described here can be applied to any spatial audio codec. The AMBIQUAL model is built on previous research described in [3,4]. In [3] we investigated, via subjective audio listening tests, the effect of compression on the listening quality and localization accuracy of single point source spatial audio sources. In [5] the impact of multi-directional audio-visual fusion on speech quality and intelligibility was explored. In [4] we proposed a full reference objective quality model for Ambisonic spatial audio, and we showed a good correlation between objective quality scores calculated with AMBIQUAL algorithm and subjective scores gathered during listening tests. This paper expands on the subjective audio listening tests presented in [3] from single point to multiple point audio sources. More complex sound scenes require further investigation and will be the topic of future work. It proposes adaptations to the AMBIQUAL algorithm where localization accuracy is calculated as a weighted product (rather than weighted sum) of similarity between reference and test Ambisonic directional channels. Lastly, it uses subjective quality scores gathered during listening tests to validate the new AMBIQUAL algorithm. Section 2 presents an introduction to Ambisonics, the Opus compression scheme for spatial audio, and the subjective experimental methodology used to evaluate and label the spatial audio samples for quality and localization accuracy. Section 3 describes the preparation of experimental samples and the subjective testing methodology employed.