Publication detail

Voice activity detection in video mediated communication from gaze

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

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/"
}