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Shazam is an application that can identify music based on a short sample played using the microphone on the device. [2] It was created by the British company Shazam Entertainment, based in London, and has been owned by Apple since 2018. The software is available for Android, macOS, iOS, Wear OS, watchOS and as a Google Chrome extension.
The latter can identify short snippets of audio (a few seconds taken from a recording), even if it is transmitted over a phone connection. Shazam uses Audio Fingerprinting for that, a technique that makes it possible to identify recordings. Musipedia, on the other hand, can identify pieces of music that contain a given melody.
Gracenote's music recognition technologies compare digital music files to a worldwide database of music information, enabling digital audio devices to identify songs. The company licenses its technologies to developers of consumer electronics devices and online media players, who integrate the technologies into media players, home and car ...
It can identify entire songs but not short snippets. [1] By 2017, the free service had 34 million "fingerprints" in-store and every day acquired between 15 and 20 thousand new entries and answered around five million search queries. AcoustID is integrated into the audio file metadata editors Picard, Jaikoz [2] and Puddletag, for example. [3] [4]
Below is a table of online music databases that are largely free of charge. Many of the sites provide a specialized service or focus on a particular music genre . Some of these operate as an online music store or purchase referral service in some capacity.
This section only includes software, not services. For services programs like Spotify, Pandora, Prime Music, etc. see Comparison of on-demand streaming music services. Likewise, list includes music RSS apps, widgets and software, but for a list of actual feeds, see Comparison of feed aggregators.
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An acoustic fingerprint is a condensed digital summary, a digital fingerprint, deterministically generated from an audio signal, that can be used to identify an audio sample or quickly locate similar items in a music database. [1]