dc.contributor.author | HAIDER, FASIH | |
dc.contributor.author | AKIRA, HAYAKAWA | |
dc.contributor.author | LUZ, SATURNINO | |
dc.contributor.author | VOGEL, CARL | |
dc.contributor.author | CAMPBELL, NICK | |
dc.contributor.editor | Hayes, M. & Ko, H. | en |
dc.date.accessioned | 2020-03-02T16:36:02Z | |
dc.date.available | 2020-03-02T16:36:02Z | |
dc.date.created | 15?20 April 2018 | en |
dc.date.issued | 2018 | |
dc.date.submitted | 2018 | en |
dc.identifier.citation | Haiderm F., Akira, H., Luz, S., Vogel, C. & Campbell, N., On-Talk and Off-Talk Detection: A Discrete Wavelet Transform Analysis of Electroencephalogram, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018) | en |
dc.identifier.other | Y | |
dc.description.abstract | Spoken interaction with a machine results in a behaviour that is not very common in face-to-face human communication: Off-Talk, which is defined as speech utterances that are not directed to an immediate interlocutor, the machine, but to another person or even oneself. It is our contention that a system which is able to detect the Off-Talk utterances can interact with a human in a more efficient manner by acknowledging that the utterances are not directed to the system and hence, not replying to Off-Talk utterances. In this paper, we demonstrate the discrimination power of a wide range of Electroencephalogram (EEG) frequency bands using wavelet transform analysis and propose models for On-Talk and Off-Talk detection using audio and EEG signals, and their fusion. Our study shows that the EEG signal can identify the occurrence of Off-Talk utterances with promising accuracy and its fusion with audio features adds a slight improvement in these results. | en |
dc.format.extent | 960-964 | en |
dc.language.iso | en | en |
dc.rights | Y | en |
dc.subject | Multimodal interaction | en |
dc.subject | Dialogue system | en |
dc.subject | Brain-computer interface | en |
dc.subject | Electroencephalogram | en |
dc.subject | On-off talk (speech) detection | en |
dc.subject | Multi-sensor fusion | en |
dc.title | On-Talk and Off-Talk Detection: A Discrete Wavelet Transform Analysis of Electroencephalogram | en |
dc.title.alternative | 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018) | en |
dc.type | Conference Paper | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/vogel | |
dc.identifier.peoplefinderurl | http://people.tcd.ie/nick | |
dc.identifier.rssinternalid | 188593 | |
dc.rights.ecaccessrights | openAccess | |
dc.subject.TCDTheme | Digital Engagement | en |
dc.subject.TCDTheme | Digital Humanities | en |
dc.subject.TCDTag | Computational linguistics | en |
dc.subject.TCDTag | DIALOG | en |
dc.subject.TCDTag | Discourse & Dialogue | en |
dc.subject.TCDTag | EEG ANALYSIS | en |
dc.subject.TCDTag | ENGAGEMENT | en |
dc.subject.TCDTag | Human-Computer Interaction | en |
dc.subject.TCDTag | interaction analysis | en |
dc.identifier.orcid_id | 0000--000-8928-8546 | |
dc.status.accessible | N | en |
dc.contributor.sponsor | Science Foundation Ireland | en |
dc.contributor.sponsorGrantNumber | 13/RC/2106 | en |
dc.identifier.uri | https://ieeexplore.ieee.org/document/8462171 | |
dc.identifier.uri | http://hdl.handle.net/2262/91669 | |