Digital audio broadcasting services transmit substantial amounts of data that is encoded to minimize bandwidth whilst maximizing user quality of experience. Many large service providers continually alter codecs to improve the encoding process. Performing subjective tests to validate each codec alteration would be impractical, necessitating the use of objective perceptual audio quality models. This paper evaluates the quality scores from ViSQOLAudio, an objective perceptual audio quality model, against the quality scores of PEAQ, POLQA, and PEMO-Q on three datasets containing fullband audio encoded with a variety of codecs and bitrates. The results show that ViSQOLAudio was more accurate than all other models on two of the datasets and performed well on the third, demonstrating the utility of ViSQOLAudio for predicting the perceptual audio quality for encoded music.Index Terms-Perceived audio quality, subjective audio quality assessment, objective audio quality assessment, ViSQOLAudio, ViSQOL, POLQA, PEAQ, PEMO-Q.
This paper describes a psycholinguistic experiment that investigates whether the applicability of the topological spatial prepositions "at", "on" or "in" to describe the spatial configuration between two objects is related to the topological relationships between objects being described.
Although data-driven spatial template models provide a practical and cognitively motivated mechanism for characterizing spatial term meaning, the influence of perceptual rather than solely geometric and functional properties has yet to be systematically investigated. In the light of this, in this paper, we investigate the effects of the perceptual phenomenon of object occlusion on the semantics of projective terms. We did this by conducting a study to test whether object occlusion had a noticeable effect on the acceptance values assigned to projective terms with respect to a 2.5-dimensional visual stimulus. Based on the data collected, a regression model was constructed and presented. Subsequent analysis showed that the regression model that included the occlusion factor outperformed an adaptation of Regier & Carlson's well-regarded AVS model for that same spatial configuration.
Utility-based control (UBC) hasn't been widely adopted for commercial game AI. Some of the reasons for this are that UBC is perceived to be: (1) resource intensive, (2) difficult to design complex behaviours with, and (3) difficult to scale for use in complex environments. This paper investigates these perceptions to see if UBC is suitable for controlling the behaviour of non-player characters in commercial games. The investigation compares agents using a UBC system against two control systems that are more frequently used in commercial games: finite state machines (FSMs), considered a simple control system, and goal-oriented action planning (GOAP), considered a complex control system. We present a case study which suggests that: (1) UBC is more resource intensive than FSMs and less than GOAP; (2) it was reasonably simple to create complex behaviours with UBC; (3) UBC didn't scale as well as FSMs or GOAP for use in complex environments.
The behaviour of non-player character game agents can be made more interesting and believable through the use of increased contextual awareness. In this paper, we present smart ambiance which allows information about the ambiance of an environment (determined by the environment itself, objects in the environment and recent events) to be used in agent plan generation. We demonstrate how this leads to contextually influenced action selection and, in turn, more interesting and believable character behaviour.
Abstract-When a user uploads audio files to a music streaming service, these files are subsequently re-encoded to lower bitrates to target different devices, e.g. low bitrate for mobile. To save time and bandwidth uploading files, some users encode their original files using a lossy codec. The metadata for these files cannot always be trusted as users might have encoded their files more than once. Determining the lowest bitrate of the files allows the streaming service to skip the process of encoding the files to bitrates higher than that of the uploaded files, saving on processing and storage space. This paper presents a model that uses quality predictions from ViSQOLAudio, a full reference objective audio quality metric, as features in combination with a multi-class support vector machine classifier. An experiment on twice-encoded files found that low bitrate codecs could be classified using audio quality features. The experiment also provides insights into the implications of multiple transcodes from a quality perspective.
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