Change search
ReferencesLink to record
Permanent link

Direct link
Online Detection Of Vocal Listener Responses With Maximum Latency Constraints
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
2011 (English)In: Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, Prague, Czech Republic, 2011, 5836-5839 p.Conference paper (Refereed)
Abstract [en]

When human listeners utter Listener Responses (e.g. back-channels or acknowledgments) such as `yeah' and `mmhmm', interlocutors commonly continue to speak or resume their speech even before the listener has finished his/her response. This type of speech interactivity results in frequent speech overlap which is common in human-human conversation. To allow for this type of speech interactivity to occur between humans and spoken dialog systems, which will result in more human-like continuous and smoother human-machine interaction, we propose an on-line classifier which can classify incoming speech as Listener Responses. We show that it is possible to detect vocal Listener Responses using maximum latency thresholds of 100-500 ms, thereby obtaining equal error rates ranging from 34% to 28% by using an energy based voice activity detector.

Place, publisher, year, edition, pages
Prague, Czech Republic, 2011. 5836-5839 p.
, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN 1520-6149
Keyword [en]
speech analysis, Speech processing
National Category
Computer Science Language Technology (Computational Linguistics)
URN: urn:nbn:se:kth:diva-52177DOI: 10.1109/ICASSP.2011.5947688ISI: 000296062406136ScopusID: 2-s2.0-80051612462ISBN: 978-145770539-7OAI: diva2:465472
36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011; Prague; 22 May 2011 through 27 May 2011
tmh_import_11_12_14 QC 20111219Available from: 2011-12-14 Created: 2011-12-14 Last updated: 2011-12-28Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Neiberg, Daniel
By organisation
Speech Communication and Technology
Computer ScienceLanguage Technology (Computational Linguistics)

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 21 hits
ReferencesLink to record
Permanent link

Direct link