gms | German Medical Science

22. Jahrestagung der Deutschen Gesellschaft für Audiologie

Deutsche Gesellschaft für Audiologie e. V.

06.03. - 09.03.2019, Heidelberg

Duration thresholds for identifying different sound types

Meeting Abstract

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  • presenting/speaker Durga Lal Budathoki - University of Canterbury, Department of Communication Disorders, Christchurch, Neuseeland
  • Greg O’Beirne - University of Canterbury, Department of Communication Disorders, Christchurch, Neuseeland

Deutsche Gesellschaft für Audiologie e.V.. 22. Jahrestagung der Deutschen Gesellschaft für Audiologie. Heidelberg, 06.-09.03.2019. Düsseldorf: German Medical Science GMS Publishing House; 2019. Doc086

doi: 10.3205/19dga086, urn:nbn:de:0183-19dga0869

Published: November 28, 2019

© 2019 Budathoki et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at



It is well known that people with hearing loss have difficulties with basic auditory processing abilities such as temporal processing, frequency selectivity, frequency discrimination, as well as difficulties with complex abilities like speech perception in noise, music perception, and environmental sound awareness. For speech perception in noise, the listener has to identify which spectro-temporal segments of the input signal are part of the target speech, and which segments belong to interfering noise. The aim of this study is to answer the following questions: what are the time thresholds required for identifying speech, music, animal sound, and noise, respectively in hearing impaired (HI) and normal hearing (NH) participants? Are these thresholds correlated to pure-tone audiometry (PTA) thresholds? Do these thresholds better predict speech intelligibility in noise, compared to PTA thresholds? The temporal detection thresholds for identifying speech, music, animal sounds and noise were measured in 16 normal-hearing participants and 27 participants with sensorineural hearing loss, using an adaptive 4 AFC-procedure. In addition, the participants underwent pure-tone audiometry and speech in noise testing using the New Zealand matrix sentence test. Our data showed that classification time thresholds were longer for HI than for NH in all sound classes except for animal sounds. Speech was classified faster than any other sound class by both NH (Median = 26.2 ms), and HI (39.8 ms). We also found a significant correlation between PTA thresholds and classification time thresholds, and speech in noise reception (SNR) thresholds and classification time thresholds for all sounds classes except animal.

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