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Subjective listening tests are routinely conducted by academic researchers and industry professionals to assess the quality of various speech and audio processing algorithms and transmission services. Listening tests often take place in controlled environments for the sake of consistency, but in many cases, listening tests could be undertaken remotely using a suitable web interface. Despite the work of several projects in the past, there is no publicly available, fully hosted listening test platform which allows for easy test creation, deployment and data collection. Here, we present a fully functional end-to-end listening test platform which allows a user to create and share MUSHRA, ACR and A/B tests within minutes. Collected data can then be downloaded in various forms. For users who would prefer to host the system on their own servers, we provide Docker and AWS images for easy installation. [ABSTRACT FROM AUTHOR]

Featured Application: Streaming spatial audio for immersive audio and virtual reality applications will require compression algorithms that maintain the localization accuracy and irrationality attributes of sound sources as well as a high-fidelity quality of experience. Models to evaluate quality will be important for media content streaming application such as YouTube as well as VR gaming and other immersive multimedia experiences. 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. [ABSTRACT FROM AUTHOR]

The article discusses how businesses have increase their budgets on information technology (IT) and their strategies for keeping their confidential data secure. It states that companies have become victims of network intrusions by sophisticated criminal organizations. It mentions surveys by Napatech and PricewaterhouseCoopers LLP (PwC) on the increase in the number of intrusions. It adds that companies have increased their IT expenditures by 90 percent.