Name
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 deviceu0027s 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. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Sound | Music recognition,Digital signal processor,Computer science,Speech recognition,Application processor,Mobile device,Fingerprint database,Battery (electricity),Detector,User privacy |
DocType | Volume | Citations |
Journal | abs/1711.10958 | 0 |
PageRank | References | Authors |
0.34 | 7 | 11 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Blaise Agüera y Arcas | 1 | 39 | 2.19 |
| Beat Gfeller | 2 | 1 | 2.38 |
| Ruiqi Guo | 3 | 13 | 3.36 |
| Kevin Kilgour | 4 | 54 | 11.00 |
| Sanjiv Kumar | 5 | 2182 | 153.05 |
| James Lyon | 6 | 0 | 0.34 |
| Julian Odell | 7 | 0 | 0.34 |
| Marvin Ritter | 8 | 14 | 2.52 |
| Dominik Roblek | 9 | 24 | 6.12 |
| Matthew Sharifi | 10 | 0 | 0.68 |
| Mihajlo Velimirovic | 11 | 0 | 0.34 |