An audio-based wakeword-independent verification system
Files
Published version
Date
2020-10-25
Authors
Wang, Joseph
Kumar, Rajath
Rodehorst, Mike
Kulis, Brian
Vitaladevuni, Shiv
Version
Published version
OA Version
Citation
Wang, J., Kumar, R., Rodehorst, M., Kulis, B., Vitaladevuni, S.N.P. (2020) An Audio-Based Wakeword-Independent Verification System. Proc. Interspeech 2020, 1952-1956, http://dx.doi.org/10.21437/Interspeech.2020-1843.
Abstract
We propose an audio-based wakeword-independent verification
model to determine whether a wakeword spotting model correctly
woke and should respond or incorrectly woke and should
not respond. Our model works on any wakeword-initiated audio,
independent of the wakeword by operating only on the audio
surrounding the wakeword, yielding a wakeword agnostic
model. This model is based on two key assumptions: that audio
surrounding the wakeword is informative to determine if the
user intended to wake the device and that this audio is independent
of the wakeword itself. We show experimentally that on
wakewords not included in the training set, our model trained
without examples or knowledge of the wakeword is able to
achieve verification performance comparable to models trained
on 5,000 to 10,000 annotated examples of the new wakeword.