On-Talk and Off-Talk Detection: A Discrete Wavelet Transform Analysis of Electroencephalogram
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2018Access:
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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)Download Item:
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.
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Grant Number
Science Foundation Ireland
13/RC/2106
Author's Homepage:
http://people.tcd.ie/vogelhttp://people.tcd.ie/nick
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Science Foundation IrelandOther Titles:
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018)Type of material:
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Multimodal interaction, Dialogue system, Brain-computer interface, Electroencephalogram, On-off talk (speech) detection, Multi-sensor fusionSubject (TCD):
Digital Engagement , Digital Humanities , Computational linguistics , DIALOG , Discourse & Dialogue , EEG ANALYSIS , ENGAGEMENT , Human-Computer Interaction , interaction analysisMetadata
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