AMBIQUAL - a full reference objective quality metric for ambisonic spatial audio

Abstract

Streaming spatial audio over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience. Streaming service providers such as YouTube need a perceptually relevant objective audio quality metric to monitor users' perceived quality and spatial localization accuracy. In this paper we introduce a full reference objective spatial audio quality metric, AMBIQUAL, which assesses both Listening Quality and Localization Accuracy. In our solution both metrics are derived directly from the B-format Ambisonic audio. The metric extends and adapts the algorithm used in ViSQOLAudio, a full reference objective metric designed for assessing speech and audio quality. In particular, Listening Quality is derived from the omnidirectional channel and Localization Accuracy is derived from a weighted sum of similarity from B-format directional channels. This paper evaluates whether the proposed AMBIQUAL objective spatial audio quality metric can predict two factors: Listening Quality and Localization Accuracy by comparing its predictions with results from MUSHRA subjective listening tests. In particular, we evaluated the Listening Quality and Localization Accuracy of First and Third-Order Ambisonic audio compressed with the OPUS 1.2 codec at various bitrates (i.e. 32, 128 and 256, 512kbps respectively). The sample set for the tests comprised both recorded and synthetic audio clips with a wide range of time-frequency characteristics. 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. Results showed a strong correlation (PCC=0.919; Spearman=0.882 regarding Listening Quality and PCC=0.854; Spearman=0.842 regarding Localization Accuracy) between objective quality scores derived from the B-format Ambisonic audio using AMBIQUAL and subjective scores obtained during listening MUSHRA tests. AMBIQUAL displays very promising quality assessment predictions for spatial audio. Future work will optimise the algorithm to generalise and validate it for any Higher Order Ambisonic formats.

Auditory Localization in Low-Bitrate Compressed Ambisonic Scenes

“…In both headphone listening cases there is no significant difference between the aforementioned bitrates and orders. These results are contrary to those found by Narbutt et al which show a significant degradation with the lowest bitrate at 3rd order [36]. We attribute these differences to the use of head-tracking and the greater localization-performance test paradigm of this study rather than perceived overall quality.…”

“…The recent version of the Opus codec (https://people.xiph.org/~jm/opus/opus-1.3) implements Channel Mapping Family 3 which allows for Ambisonic signal coupling [34]. Previous work by Narbutt et al includes subjective evaluation of Ambisonics compressed with Opus 1.2 codec with Channel Mapping Family 2 implementation [35] and the development of a reference objective spatial audio quality metric [36]. They use a MUSHRA paradigm to assess the localization degradation and demonstrate quality degradation between equivalent bitrates at different orders.…”

Human-centric Quality Management of Immersive Multimedia Applications

“…Narbutt et al [17] ViSQOL Audio Audio (traditional) Narbutt et al [17] ViSQOL Speech Audio (speech) Narbutt et al [17] AMBIQUAL Audio (ambisonics) Sakr et al [18] HPWPSNR Haptics Hassen et al [19] HSSIM Haptics rameters on the appearance of cybersickness can be assessed. In addition, the sensors embedded within the Head-Mounted Device (HMD) can be exploited to measure indications of cybersickness such as eye tracking (drop of attention) and tactile sensors (drop in pointing accuracy).…”

“…For auditory feeds, there also exist a handful of metrics such as ViSQOL Audio, ViSQOL Speech and AMBIQUAL by Narbutt et al [17] for traditional audio, speech and ambisonics (i.e. a full sphere audio surrounding technique) respectively.…”

Design and Testing of a Real-Time Audio-Quality Feedback System for Weather Broadcasts and a Framework for a Weather Broadcast Transmission Technology Switch

“…Narbutt et al (2018) [12] have proposed an objective spatial audio quality metric that can predict listening quality and localization accuracy. Their solution, based on the ViSQO-LAudio algorithm, aims at streaming services like YouTube.…”