The idea to programatically identify music by it listening to it. My goal is to start reading people's tango music libraries to get a full cache of what song is what, and what year, and other information. Sometimes songs are mislabeled on CD's, but more importantly they usually don't have year information. This is an attempt to resolve that. But it has the side benefit of allowing to figure out "what am I listening to?!"
They say that it is a fast and free audio fingerprinting service. This seems to be the best first bet on making something that works. Has a Java example on how to compare two fingerprints. They also have libraries and the full source code.
It is an attempt at a comprehensive music information site. They have a link of known audio fingerprinting systems.
"Marsyas (Music Analysis, Retrieval and Synthesis for Audio Signals) is a framework for developing systems for audio processing. It provides an general architecture for connecting audio, soundfiles, signal processing blocks and machine learning."
Wikipedia entry on Acoustic fingerprinting.
Wapedia is an encyclopedia for mobile devices. Has a bunch of good links here too.
"MusicDNS provides a simple, easy to use method for acoustically identifying digital music and acquiring the correct metadata. Leveraging patented acoustic recognition technology, MusicDNS consistently identifies the same digital music recording, regardless language or audio file format."
In theory what I am looking to end up doing, but this is simply a download option, no response back feature.
A Columbia University project in MATLAB to identify a song, regardless of who is playing it. This attempts to figure out "what is this a cover of?"
Automatic Song Identification in Noisy Broadcast Audio
Paper on how to identify a song that is being rebroadcast.
"Automatic identification of music titles and copyright enforcement of audio material has become a topic of great interest. One of the main problems with broadcast audio is that the received audio suffers several transformations before reaching the listener (equalizations, noise, speaker over the audio, parts of the songs are changed or removed, etc.) and, therefore, the original and the broadcast songs are very different from the signal point of view."
A thesis on how to do song id'ing using "the Numenta Platform".