scholarly journals AMBIQUAL: Towards a Quality Metric for Headphone Rendered Compressed Ambisonic Spatial Audio

2020 ◽  
Vol 10 (9) ◽  
pp. 3188
Author(s):  
Miroslaw Narbutt ◽  
Jan Skoglund ◽  
Andrew Allen ◽  
Michael Chinen ◽  
Dan Barry ◽  
...  

Spatial audio is essential for creating a sense of immersion in virtual environments. Efficient encoding methods are required to deliver spatial audio over networks without compromising Quality of Service (QoS). Streaming service providers such as YouTube typically transcode content into various bit rates and need a perceptually relevant audio quality metric to monitor users’ perceived quality and spatial localization accuracy. The aim of the paper is two-fold. First, it is to investigate the effect of Opus codec compression on the quality of spatial audio as perceived by listeners using subjective listening tests. Secondly, it is to introduce AMBIQUAL, a full reference objective metric for spatial audio quality, which derives both listening quality and localization accuracy metrics directly from the B-format Ambisonic audio. We compare AMBIQUAL quality predictions with subjective quality assessments across a variety of audio samples which have been compressed using the Opus 1.2 codec at various bit rates. Listening quality and localization accuracy of first and third-order Ambisonics were evaluated. Several fixed and dynamic audio sources (single and multiple) were used to evaluate localization accuracy. Results show good correlation regarding listening quality and localization accuracy between objective quality scores using AMBIQUAL and subjective scores obtained during listening tests.

Author(s):  
Farah Diyana Abdul Rahman ◽  
Dimitris Agrafiotis ◽  
Ahmad Imran Ibrahim

In multimedia transmission, it is important to rely on an objective quality metric which accurately represents the subjective quality of processed images and video sequences. Reduced-reference metrics make use of side-information that is transmitted to the receiver for estimating the quality of the received sequence with low complexity. In this paper, an Edge-based Dissimilarity Reduced-Reference video quality metric with low overhead bitrate is proposed. The metric is evaluated by finding the dissimilarity between the edge information of original and distorted sequences. The edge degradation can be detected in this manner as perceived video quality is highly associated with edge structural. Due to the high overhead using the Soergel distance, it is pertinent to find a way to reduce the overhead while maintaining the edge information that can convey the quality measure of the sequences. The effects of different edge detection operator, video resolution and file compressor are investigated. The aim of this paper is to significantly reduce the bitrate required in order to transmit the side information overhead as the reduced reference video quality metric. From the results obtained, the side information extracted using Sobel edge detector maintained consistency throughout the reduction of spatial and temporal down-sample.


2013 ◽  
Vol 38 (1) ◽  
pp. 55-62 ◽  
Author(s):  
Shu-Nung Yao ◽  
Li Jen Chen

Abstract There are an increasing number of binaural systems embedded with head-related transfer functions (HRTFs), so listeners can experience virtual environments via conventional stereo loudspeakers or head- phones. As HRTFs vary from person to person, it is difficult to select appropriated HRTFs from already existing databases for users. Once the HRTFs in a binaural audio device hardly match the real ones of the users, poor localization happens especially on the cone of confusion. The most accurate way to obtain personalized HRTFs might be doing practical measurements. It is, however, expensive and time consuming. Modifying non-individualized HRTFs may be an effort-saving way, though the modifications are always accompanied by undesired audio distortion. This paper proposes a flexible HRTF adjustment system for users to define their own HRTFs. Also, the system can keep sounds from suffering intolerable distortion based on an objective measurement tool for evaluating the quality of processed audio.


2017 ◽  
Vol 42 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Przemysław Gilski ◽  
Jacek Stefański

Abstract Broadcasting services seek to optimize their use of bandwidth in order to maximize user’s quality of experience. They aim to transmit high-quality digital speech and music signals at the lowest bitrate. They intend to offer the best quality under available conditions. Due to bandwidth limitations, audio quality is in conflict with the number of transmitted radio programs. This paper analyzes whether the quality of real-time digital DAB+ broadcasted radio programs surpasses the quality offered by analog FM radio. We also perform a subjective and objective quality assessment comparative study of the HE-AAC v2 audio codec used in DAB+. The subjective studies were carried out using the MOS test methodology, whereas the objective tests were realized using the ViSQOLAudio metric. These studies were followed by a questionnaire concerning the migration from analog to digital radio domain.


2021 ◽  
Author(s):  
Alireza Javaheri ◽  
Catarina Brites ◽  
Fernando Pereira ◽  
Joao Ascenso

Point cloud coding solutions have been recently standardized to address the needs of multiple application scenarios. The design and assessment of point cloud coding methods require reliable objective quality metrics to evaluate the level of degradation introduced by compression or any other type of processing. Several point cloud objective quality metrics has been recently proposed to reliable estimate human perceived quality, including the so-called projection-based metrics. In this context, this paper proposes a joint geometry and color projection-based point cloud objective quality metric which solves the critical weakness of this type of quality metrics, i.e., the misalignment between the reference and degraded projected images. Moreover, the proposed point cloud quality metric exploits the best performing 2D quality metrics in the literature to assess the quality of the projected images. The experimental results show that the proposed projection-based quality metric offers the best subjective-objective correlation performance in comparison with other metrics in the literature. The Pearson correlation gains regarding D1-PSNR and D2-PSNR metrics are 17% and 14.2 when data with all coding degradations is considered.


Author(s):  
Michael Arnold

Methods for evaluating the quality of watermarked objects are detailed in this chapter. It will provide an overview of subjective and objective methods usable in order to judge the influence of watermark embedding on the quality of audio tracks. The problem associated with the quality evaluation of watermarked audio data will be presented. This is followed by a presentation of subjective evaluation standards used in testing the transparency of marked audio tracks as well as the evaluation of marked items with intermediate quality. Since subjective listening tests are expensive and dependent on many not easily controllable parameters, objective quality measurement methods are discussed in section Objective Evaluation Standards. Section Implementation of a Quality Evaluation presents the whole process of testing the quality taking into account the methods discussed in this chapter. Special emphasis is devoted to a detailed description of the test setup, item selection and the practical limitations. The last section summarizes the chapter.


2021 ◽  
Author(s):  
Alireza Javaheri ◽  
Catarina Brites ◽  
Fernando Pereira ◽  
Joao Ascenso

Point cloud coding solutions have been recently standardized to address the needs of multiple application scenarios. The design and assessment of point cloud coding methods require reliable objective quality metrics to evaluate the level of degradation introduced by compression or any other type of processing. Several point cloud objective quality metrics has been recently proposed to reliable estimate human perceived quality, including the so-called projection-based metrics. In this context, this paper proposes a joint geometry and color projection-based point cloud objective quality metric which solves the critical weakness of this type of quality metrics, i.e., the misalignment between the reference and degraded projected images. Moreover, the proposed point cloud quality metric exploits the best performing 2D quality metrics in the literature to assess the quality of the projected images. The experimental results show that the proposed projection-based quality metric offers the best subjective-objective correlation performance in comparison with other metrics in the literature. The Pearson correlation gains regarding D1-PSNR and D2-PSNR metrics are 17% and 14.2 when data with all coding degradations is considered.


Author(s):  
Sheyda Kiani Mehr ◽  
Prasad Jogalekar ◽  
Deep Medhi

AbstractObjective Quality of Experience (QoE) for Dynamic Adaptive Streaming over HTTP (DASH) video streaming has received considerable attention in recent years. While there are a number of objective QoE models, a limitation of the current models is that the QoE is provided after the entire video is delivered; also, the models are on a per client basis. For content service providers, QoE observed is important to monitor to understand ensemble performance during streaming such as for live events or concurrent streaming when multiple clients are streaming. For this purpose, we propose Moving QoE (MQoE, in short) models to measure QoE during periodically during video streaming for multiple simultaneous clients. Our first model MQoE_RF is a nonlinear model considering the bitrate gain and sensitivity from bitrate switching frequency. Our second model MQoE_SD is a linear model that focuses on capturing the standard deviation in the bitrate switching magnitude among segments along with the bitrate gain. We then study the effectiveness of both models in a multi-user mobile client environment, with the mobility patterns being based on traces from a train, a car, or a ferry. We implemented the study on the GENI testbed. Our study shows that our MQoE models are more accurate in capturing the QoE behavior during transmission than static QoE models. Furthermore, our MQoE_RF model captures the sensitivity due to bitrate switching frequency more effectively while MQoE_SD captures the sensitivity due to the magnitude of the bitrate switching. Either models are suitable for content service providers for monitoring video streaming based on their preference.


Author(s):  
Chatwadee Tansakul ◽  
◽  
Jirachai Buddhakulsomsiri ◽  
Thananya Wasusri ◽  
Papusson Chaiwat ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document