Navigation auf zora.uzh.ch

Search

ZORA (Zurich Open Repository and Archive)

Listeners use temporal information to identify French- and English-accented speech

Kolly, Marie-José; Boula de Mareüil, Philippe; Leemann, Adrian; Dellwo, Volker (2017). Listeners use temporal information to identify French- and English-accented speech. Speech Communication, 86:121-134.

Abstract

Which acoustic cues can be used by listeners to identify speakers’ linguistic origins in foreign-accented speech? We investigated accent identification performance in signal-manipulated speech, where (a) Swiss German listeners heard native German speech to which we transplanted segment durations of French-accented German and English-accented German, and (b) Swiss German listeners heard 6-band noise-vocoded French-accented and English-accented German speech to which we transplanted native German segment durations. Therefore, the foreign accent cues in the stimuli consisted of only temporal information (in a) and only strongly degraded spectral information (in b). Findings suggest that listeners were able to identify the linguistic origin of French and English speakers in their foreign-accented German speech based on temporal features alone, as well as based on strongly degraded spectral features alone. When comparing these results to previous research, we found an additive trend of temporal and spectral cues: identification performance tended to be higher when both cues were present in the signal. Acoustic measures of temporal variability could not easily explain the perceptual results. However, listeners were drawn towards some of the native German segmental cues in condition (a), which biased responses towards ‘French’ when stimuli featured uvular /r/s and towards ‘English’ when they contained vocalized /r/s or lacked /r/.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Department of Comparative Language Science
06 Faculty of Arts > Institute of Computational Linguistics
06 Faculty of Arts > Zurich Center for Linguistics
Dewey Decimal Classification:490 Other languages
890 Other literatures
410 Linguistics
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Modeling and Simulation
Social Sciences & Humanities > Communication
Social Sciences & Humanities > Language and Linguistics
Social Sciences & Humanities > Linguistics and Language
Physical Sciences > Computer Vision and Pattern Recognition
Physical Sciences > Computer Science Applications
Uncontrolled Keywords:Linguistics and Language, Modelling and Simulation, Software, Communication, Computer Vision and Pattern Recognition, Language and Linguistics, Computer Science Applications
Language:English
Date:2017
Deposited On:09 Jan 2017 13:57
Last Modified:15 Sep 2024 01:39
Publisher:Elsevier
ISSN:0167-6393
Funders:Swiss National Science Foundation, Gebert Rüf Stiftung
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.specom.2016.11.006
Project Information:
  • Funder: SNSF
  • Grant ID:
  • Project Title: Swiss National Science Foundation
  • Funder:
  • Grant ID:
  • Project Title: Gebert Rüf Stiftung

Metadata Export

Statistics

Citations

Dimensions.ai Metrics
3 citations in Web of Science®
4 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

7 downloads since deposited on 09 Jan 2017
0 downloads since 12 months
Detailed statistics

Authors, Affiliations, Collaborations

Similar Publications