Now Playing: Continuous low-power music recognition
Blaise Ag\"uera y Arcas, Beat Gfeller, Ruiqi Guo, Kevin Kilgour,, Sanjiv Kumar, James Lyon, Julian Odell, Marvin Ritter, Dominik Roblek,, Matthew Sharifi, Mihajlo Velimirovi\'c

TL;DR
This paper introduces Now Playing, a low-power, on-device music recognition system that continuously detects and identifies music on mobile devices with minimal battery usage and without requiring server connectivity.
Contribution
The paper presents a novel on-device music recognition system that operates continuously with low power consumption, eliminating the need for server-based processing.
Findings
Uses less than 1% battery daily on average
Runs entirely on-device, ensuring user privacy
Passively recognizes a wide range of music
Abstract
Existing music recognition applications require 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 device and automatically recognizes music without user interaction. To reduce battery consumption, a small music detector runs continuously on the mobile device's DSP chip and wakes up the main application processor only when it is confident that music is present. Once woken, the recognizer on the application processor is provided with a few seconds of audio which is fingerprinted and compared to the stored fingerprints in the on-device fingerprint database of tens of thousands of songs. Our presented system, Now Playing, has a daily battery usage of less than 1% on average, respects user privacy by running entirely on-device and can passively recognize a wide range of music.
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Taxonomy
TopicsMusic and Audio Processing · Speech and Audio Processing · Music Technology and Sound Studies
