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

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.