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HRADIŠ, M. EIVAZI, S. BEDNAŘÍK, R.
Original Title
Voice activity detection in video mediated communication from gaze
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
This paper discuses prediction of active speaker in multi-party video mediated communication from gaze data. In the explored setting, we predict voice activity of participants in one room based on gaze recordings of a single participant in another room. The two rooms were connected by high definition and low delay audio and video links and the participants engaged in different activities ranging from casual discussion to simple casual games. We treat the task as classification problem. We evaluate different types of features and parameter setting in the context of Support Vector Machine classification framework. The results show that the speaker activity can be correctly predicted with the proposed approach in 90 % of the time for which the gaze data are available.
Keywords
gaze tracking, voice activity detection, speaker recog-nition, machine learning, Support Vector Machines
Authors
HRADIŠ, M.; EIVAZI, S.; BEDNAŘÍK, R.
RIV year
2012
Released
28. 3. 2012
Publisher
Association for Computing Machinery
Location
Santa Barbara
ISBN
978-1-4503-1221-9
Book
ETRA '12 Proceedings of the Symposium on Eye Tracking Research and Applications
Pages from
329
Pages to
332
Pages count
6
URL
https://www.fit.vut.cz/research/publication/9861/
BibTex
@inproceedings{BUT91461, author="Michal {Hradiš} and Shahram {Eivazi} and Roman {Bednařík}", title="Voice activity detection in video mediated communication from gaze", booktitle="ETRA '12 Proceedings of the Symposium on Eye Tracking Research and Applications", year="2012", pages="329--332", publisher="Association for Computing Machinery", address="Santa Barbara", doi="10.1145/2168556.2168628", isbn="978-1-4503-1221-9", url="https://www.fit.vut.cz/research/publication/9861/" }