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Personalized Object-Based Audio for Hearing Impaired TV Viewers
Author(s) -
Ben Shirley,
Melissa G. Meadows,
Fadi Malak,
James Woodcock,
Ash Tidball
Publication year - 2017
Publication title -
journal of the audio engineering society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.234
H-Index - 60
ISSN - 1549-4950
DOI - 10.17743/jaes.2017.0005
Subject(s) - personalization , categorization , object (grammar) , computer science , multimedia , population , psychology , audiology , speech recognition , artificial intelligence , medicine , world wide web , environmental health
Age demographics have led to an increase in the proportion of the population suffering from some form of hearing loss. The introduction of object-based audio to television broadcast has the potential to improve the viewing experience for millions of hearing impaired people. Personalization of object-based audio can assist in overcoming difficulties in understanding speech and understanding the narrative of broadcast media. The research presented here documents a Multi-Dimensional Audio (MDA) implementation of object-based clean audio to present independent object streams based on object category elicitation. Evaluations were carried out with hearing impaired people and participants were able to personalize audio levels independently for four object-categories using an on-screen menu: speech, music, background effects and foreground effects related to on-screen events. Results show considerable preference variation across subjects but indicate that expanding object-category personalization beyond a binary speech/non-speech categorization can substantially improve the viewing experience for some hearing impaired people.

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