Objective Assessment of Perceptual Audio Quality Using ViSQOLAudio

Sloan, Colm; Harte, Naomi; Kelly, Damien P.; Kokaram, Anil; Hines, Andrew

doi:10.1109/tbc.2017.2704421

Cited by 44 publications

(33 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Results show that audio channel compression can greatly impact both Listening Quality and Localization Accuracy. These results will be used to validate and optimise work currently underway to develop a full reference objective spatial audio quality metric adapted from ViSQOLAudio [9], [10].…”

Section: Discussionmentioning

confidence: 99%

“…This paper presents the results of experiments that explore the relationship between audio quality and localisation accuracy for uncompressed audio and OPUS-compressed audio samples. The results will be used to validate and optimise work currently underway to develop a full reference objective spatial audio quality metric adapted from ViSQOLAudio [9], [10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Streaming VR for immersion: Quality aspects of compressed spatial audio

Narbutt¹,

O’Leary²,

Allen

et al. 2017

2017 23rd International Conference on Virtual System &Amp; Multimedia (VSMM)

Self Cite

View full text Add to dashboard Cite

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 setup. 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.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Streaming VR for immersion: Quality aspects of compressed spatial audio

Narbutt¹,

O’Leary²,

Allen

et al. 2017

2017 23rd International Conference on Virtual System &Amp; Multimedia (VSMM)

Self Cite

View full text Add to dashboard Cite

show abstract

“…We still conducted this evaluation to understand the performance with an objective quality predictor. We computed the mean opinion score -listening quality objective (MOS-LQO) measures predicted by ViSQOLAudio (ViA) [30]. We found ViA to be suitable for our purpose as it was designed to predict the quality of both speech and audio.…”

Section: Objective Evaluationmentioning

confidence: 99%

Audio Codec Enhancement with Generative Adversarial Networks

Biswas¹,

Jia²

2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

Audio codecs are typically transform-domain based and efficiently code stationary audio signals, but they struggle with speech and signals containing dense transient events such as applause. Specifically, with these two classes of signals as examples, we demonstrate a technique for restoring audio from coding noise based on generative adversarial networks (GAN). A primary advantage of the proposed GAN-based coded audio enhancer is that the method operates end-to-end directly on decoded audio samples, eliminating the need to design any manually-crafted frontend. Furthermore, the enhancement approach described in this paper can improve the sound quality of low-bit rate coded audio without any modifications to the existent standard-compliant encoders. Subjective tests illustrate that the proposed enhancer improves the quality of speech and difficult to code applause excerpts significantly.

show abstract

“…FR model for audio quality assessment modeling the human speech quality perception using a spectro-temporal measure of similarity [19] POLQA (Perceptual Objective Listening Quality Analysis)…”

Section: Psnr (Peak Signal-to-noise Ratio)mentioning

confidence: 99%

Assessment of QoE for Video and Audio in WebRTC Applications Using Full-Reference Models

et al. 2020

Self Cite

View full text Add to dashboard Cite

WebRTC is a set of standard technologies that allows exchanging video and audio in real time on the Web. As with other media-related applications, the user-perceived audiovisual quality can be estimated using Quality of Experience (QoE) measurements. This paper analyses the behavior of different objective Full-Reference (FR) models for video and audio in WebRTC applications. FR models calculate the video and audio quality by comparing some original media reference with the degraded signal. To compute these models, we have created an open-source benchmark in which different types of reference media inputs are sent browser to browser while simulating different kinds of network conditions in terms of packet loss and jitter. Our benchmark provides recording capabilities of the impairment WebRTC streams. Then, we use different existing FR metrics for video (VMAF, VIFp, SSIM, MS-SSIM, PSNR, PSNR-HVS, and PSNR-HVS-M) and audio (PESQ, ViSQOL, and POLQA) recordings together with their references. Moreover, we use the same recordings to carry out a subjective analysis in which real users rate the video and audio quality using a Mean Opinion Score (MOS). Finally, we calculate the correlations between the objective and subjective results to find the objective models that better correspond with the subjective outcome, which is considered the ground truth QoE. We find that some of the studied objective models, such as VMAF, VIFp, and POLQA, show a strong correlation with the subjective results in packet loss scenarios.

show abstract

Objective Assessment of Perceptual Audio Quality Using ViSQOLAudio

Cited by 44 publications

References 16 publications

Streaming VR for immersion: Quality aspects of compressed spatial audio

Streaming VR for immersion: Quality aspects of compressed spatial audio

Audio Codec Enhancement with Generative Adversarial Networks

Assessment of QoE for Video and Audio in WebRTC Applications Using Full-Reference Models

Contact Info

Product

Resources

About