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ABSTRACT
Imagine the following situation. You’re in your car, listening to
留学生论文网the radio and suddenly you hear a song that catches your attention.
It’s the best new song you have heard for a long time, but youmissed the announcement and don’t recognize the artist. Still, you
would like to know more about this music. What should you do?
You could call the radio station, but that’s too cumbersome.
Wouldn’t it be nice if you could push a few buttons on your
mobile phone and a few seconds later the phone would respondwith the name of the artist and the title of the music you’re
listening to? Perhaps even sending an email to your default emailaddress with some supplemental information. In this paper wepresent an audio fingerprinting system, which makes the abovescenario possible. By using the fingerprint of an unknown audioclip as a query on a fingerprint database, which contains thefingerprints of a large library of songs, the audio clip can beidentified. At the core of the presented system are a highly robustfingerprint extraction method and a very efficient fingerprintsearch strategy, which enables searching a large fingerprint
database with only limited computing resources.
1. INTRODUCTION
Fingerprint systems are over one hundred years old. In 1893 Sir
Francis Galton was the first to “prove” that no two fingerprints of
human beings were alike. Approximately 10 years later Scotland
Yard accepted a system designed by Sir Edward Henry foridentifying fingerprints of people. This system relies on the patternof dermal ridges on the fingertips and still forms the basis of all“human” fingerprinting techniques of today. This type of forensic“human” fingerprinting system has however existed for longerthan a century, as 2000 years ago Chinese emperors were alreadyusing thumbprints to sign important documents. The implication isthat already those emperors (or at least their administrativeservants) realized that every fingerprint was unique. Conceptuallya fingerprint can be seen as a “human” summary or signature thatis unique for every human being. It is important to note that ahuman fingerprint differs from a textual summary in that it doesnot allow the reconstruction of other aspects of the original. Forexample, a human fingerprint does not convey any informationabout the color of the person’s hair or eyes.
Recent years have seen a growing scientific and industrial interestin computing fingerprints of multimedia objects [1][2][3][4]
[5][6]. The growing industrial interest is shown among others by a
large number of (startup) companies [7][8][9][10][11][12][13]
and the recent request for information on audio fingerprinting
technologies by the International Federation of the Phonographic
Industry (IFPI) and the Recording Industry Association of
America (RIAA) [14].
The prime objective of multimedia fingerprinting is an efficient
mechanism to establish the perceptual equality of two multimedia
objects: not by comparing the (typically large) objects themselves,
but by comparing the associated fingerprints (small by design). In
most systems using fingerprinting technology, the fingerprints of a
large number of multimedia objects, along with their associated
meta-data (e.g. name of artist, title and album) are stored in a
database. The fingerprints serve as an index to the meta-data. The
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