Open AccessPerceptual Dimensions Underlying Tinnitus-Like Sounds
Author(s) -
Jennifer J. Lentz,
Yunhua He
Publication year - 2020
Publication title -
journal of speech, language, and hearing research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 138
eISSN - 1558-9102
pISSN - 1092-4388
DOI - 10.1044/2020_jslhr-19-00327
Subject(s) - multidimensional scaling , perception , tinnitus , speech recognition , noise (video) , similarity (geometry) , psychology , set (abstract data type) , cluster analysis , auditory perception , hierarchical clustering , audiology , computer science , acoustics , pattern recognition (psychology) , artificial intelligence , cognitive psychology , physics , machine learning , medicine , neuroscience , psychiatry , image (mathematics) , programming language
Purpose The goal of this study was to establish the perceptual underpinnings of the terms that are commonly used by patients when describing the quality of their tinnitus. Method Using a free-classification method, 15 subjects with normal hearing placed 60 different tinnitus-like sounds into similarity clusters on a grid. Multidimensional scaling, hierarchical clustering, and acoustic analyses were used to determine the acoustic underpinnings of the perceptual dimensions and perceptual similarity. Results Multidimensional scaling revealed three different perceptual dimensions (pitch, modulation depth + spectral elements, and envelope rate). Hierarchical clustering revealed five explicit similarity clusters: tonal, steady noise, pulsatile, low-frequency fluctuating noise, and high-frequency fluctuating. Conclusions Results are consistent with tinnitus perceptions falling into a small set of categories that can be characterized by their acoustics. As a result, there is the potential to develop different tools to assess tinnitus using a variety of different sounds.