On-Talk and Off-Talk Detection: A Discrete Wavelet Transform Analysis of Electroencephalogram

Fasih Haider; Hayakawa Akira; Saturnino Luz; Carl Vogel; Nick Campbell

ICASSP 2018accepted0 citations

On-Talk and Off-Talk Detection: A Discrete Wavelet Transform Analysis of Electroencephalogram

Fasih Haider, Hayakawa Akira, Saturnino Luz, Carl Vogel, Nick Campbell

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.

BibTeX

@inproceedings{icassp2018_ontalkandofftalk,
  title = {On-Talk and Off-Talk Detection: A Discrete Wavelet Transform Analysis of Electroencephalogram},
  author = {Fasih Haider and Hayakawa Akira and Saturnino Luz and Carl Vogel and Nick Campbell},
  booktitle = {ICASSP 2018},
  year = {2018}
}