Shazam Style Automatic Signal Identification via the Sigidwiki Database

audio recognition system

Thank you to José Carlos Rueda for submitting news about his work on converting a “Shazam”-like Python program made originally for song identification into a program that can be used to automatically identify radio signals based on their demodulated audio sounds. Shazam is a popular app for smartphones that can pull up the name of any song playing within seconds via the microphone. It works by using audio fingerprinting algorithms and a database of stored song fingerprints.

Using similar algorithm to Shazam, programmer Joseph Balikuddembe created an open source program called “audio_recogition_system” [sic] which was designed for creating your own audio fingerprint databases out of any mp3 files.

José then had the clever idea to take the database of signal sounds from sigidwiki.com, and create an identification database of signal sounds for audio_recogition_system. He writes that from his database the program can now identify up to 350 known signals from the sigidwiki database. His page contains the installation instructions and a link to download his premade database. The software can identify via audio that is input from the PC microphone/virtual audio cable or from a file.

Fingerprinted Audio Samples of Radio Signals
Fingerprinted Audio Samples of Radio Signals