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Title: Multi-listener auditory displays
Author: Lunn, Paul
ISNI:       0000 0004 7658 7928
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2016
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This thesis investigates how team working principles can be applied to Auditory Displays (AD). During this work it was established that there the level of collaboration and team work within the AD community was low and that this community would benefit from a enhanced collaborative approach. The increased use of collaborative techniques will benefit the AD community by increasing quality, knowledge transfer, synergy, and enhancing innovation. The reader is introduced to a novel approach to collaborative AD entitled Multi-listener Auditory Displays (MLAD). This work focused upon two areas of MLAD distributed AD teams and virtual AD teams. A distributed AD team is a team of participants who work upon a common task at different times and locations. The distributed approach was found to work effectively when designing ADs that work upon large scale data sets such as that found in big data. A virtual AD team is a group of participants who work upon a common task simultaneously and in separate locations. A virtual AD team is assisted by computer technology such as video conferencing and email. The virtual auditory display team was found to work well by enabling a team to work more effectively together who were geographically spread. Two pilot studies are included; SonicSETI is an example of a distributed AD team, where a remote group of listeners have background white noise playing, and use passive listening to detect anomalous candidate signals; and a geographically diverse virtual AD team that collaborates through electronic technology on an auditory display which sonifies a database of red wine measurements. A workshop was organised at a conference which focused upon ensemble auditory displays with a group of participants who were co- located.
Supervisor: Hunt, Andy Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available