Now Playing: Continuous low-power music recognition
Venue
NIPS 2017 Workshop: Machine Learning on the Phone
Publication Year
2017
Authors
Beat Gfeller, Blaise Aguera-Arcas, Dominik Roblek, James David Lyon, Julian James Odell, Kevin Kilgour, Marvin Ritter, Matt Sharifi, Mihajlo Velimirović, Ruiqi Guo, Sanjiv Kumar
BibTeX
Abstract
Existing music recognition applications require both user activation and a
connection to a server that performs the actual recognition. In this paper we
present a low power music recognizer that runs entirely on a mobile phone and
automatically recognizes music without requiring any user activation. A small music
detector runs continuously on the mobile phone’s DSP (digital signal processor)
chip and only wakes main the processor when it is confident that music is present.
Once woken the detector on the main processor is provided with an 8s buffer of
audio which is then fingerprinted and compared to the stored fingerprints in the
on-device fingerprint database of over 70000 songs.