Towards a Listener Model for Predicting the Overall Listening Experience
Schöffler M, Herre J (2014)
Publication Type: Conference contribution
Publication year: 2014
Publisher: Association for Computing Machinery
Edited Volumes: ACM International Conference Proceeding Series
Series: ICPS: ACM International Conference Proceeding Series
Conference Proceedings Title: Proceedings of the 9th Audio Mostly: A Conference on Interaction With Sound
Event location: Aalborg
ISBN: 978-1-4503-3032-9; DOI: 10.1145/2636879.2636892
URI: http://dl.acm.org/citation.cfm?id=2636892
Abstract
Listeners have different preferences when it comes to rating the overall listening experience while listening to music. Therefore, a listener model for predicting the overall listening experience must consider sensory, perceptual, cognitive and psychological aspects rather than solely rely on perception-based attributes (e. g. audio quality) of the music signal. In this work, a generic model framework is defined for modeling a listener while taking part in an auditory experiment. In addition, a subset of the model is used to describe algorithms for predicting the overall listening experience based on experimental results. Thereby, the results of two experiments are utilized to define a prediction algorithm for the cases of bandwidth-degradation stimuli and playback by different reproduction systems.
Authors with CRIS profile
Michael Schöffler
Lehrstuhl für Audiocodierung (AudioLabs) (Stiftungslehrstuhl)
Jürgen Herre
Lehrstuhl für Audiocodierung (AudioLabs) (Stiftungslehrstuhl)
How to cite
APA:
Schöffler, M., & Herre, J. (2014). Towards a Listener Model for Predicting the Overall Listening Experience. In Proceedings of the 9th Audio Mostly: A Conference on Interaction With Sound. Aalborg, DK: Association for Computing Machinery.
MLA:
Schöffler, Michael, and Jürgen Herre. "Towards a Listener Model for Predicting the Overall Listening Experience." Proceedings of the 9th Audio Mostly: A Conference on Interaction with Sound, AM 2014, Aalborg Association for Computing Machinery, 2014.
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