%0 Journal Article %A Searchfield, Grant D. %A Linford, Tania %A Kobayashi, Kei %A Crowhen, David %A Latzel, Matthias %D 2017 %T The performance of an automatic acoustic-based program classifier compared to hearing aid users’ manual selection of listening programs %U https://tandf.figshare.com/articles/journal_contribution/The_performance_of_an_automatic_acoustic-based_program_classifier_compared_to_hearing_aid_users_manual_selection_of_listening_programs/5539633 %R 10.6084/m9.figshare.5539633.v1 %2 https://tandf.figshare.com/ndownloader/files/9591859 %K Hearing aid %K trial %K digital signal processing %X

Objective: To compare preference for and performance of manually selected programmes to an automatic sound classifier, the Phonak AutoSense OS. Design: A single blind repeated measures study. Participants were fit with Phonak Virto V90 ITE aids; preferences for different listening programmes were compared across four different sound scenarios (speech in: quiet, noise, loud noise and a car). Following a 4-week trial preferences were reassessed and the users preferred programme was compared to the automatic classifier for sound quality and hearing in noise (HINT test) using a 12 loudspeaker array. Study sample: Twenty-five participants with symmetrical moderate-severe sensorineural hearing loss. Results: Participant preferences of manual programme for scenarios varied considerably between and within sessions. A HINT Speech Reception Threshold (SRT) advantage was observed for the automatic classifier over participant’s manual selection for speech in quiet, loud noise and car noise. Sound quality ratings were similar for both manual and automatic selections. Conclusions: The use of a sound classifier is a viable alternative to manual programme selection.

%I Taylor & Francis