Authors
Hannah White, Joshua Penney, Andy Gibson, Anita Szakay, Felicity Cox
Publication date
2022/9/1
Journal
The Journal of the Acoustical Society of America
Volume
152
Issue
3
Pages
1476-1486
Publisher
AIP Publishing
Description
There is growing interest in research on the non-modal voice quality, creaky voice; however, its identification often relies on time-consuming manual annotation, leading to a recent focus on automatic creak detection methods. Various automatic methods have been proposed, which rely on varying types and combinations of acoustic cues for creak detection. In this paper, we compare the performance of three automatic tools, the AntiMode method, the Creak Detector algorithm, and the Roughness algorithm, against manual annotation of creak using data from 80 Australian English speakers. We explore the possibility that tools used in combination may yield more accurate creak detection than individual tools used alone. Based on method comparisons, we present options for researchers, including an “out-of-the-box” approach, which supports combining automatic tools, and propose additional steps to further improve …
Total citations
202220232024232
Scholar articles
H White, J Penney, A Gibson, A Szakay, F Cox - The Journal of the Acoustical Society of America, 2022