Journal article
Acoustic and linguistic features influence talker change detection
Abstract
A listening test is proposed in which human participants detect talker changes in two natural, multi-talker speech stimuli sets-a familiar language (English) and an unfamiliar language (Chinese). Miss rate, false-alarm rate, and response times (RT) showed a significant dependence on language familiarity. Linear regression modeling of RTs using diverse acoustic features derived from the stimuli showed recruitment of a pool of acoustic features …
Authors
Sharma NK; Krishnamohan V; Ganapathy S; Gangopadhayay A; Fink L
Journal
The Journal of the Acoustical Society of America, Vol. 148, No. 5, pp. el414–el419
Publisher
Acoustical Society of America (ASA)
Publication Date
November 1, 2020
DOI
10.1121/10.0002462
ISSN
0001-4966