EDAmazing: An audio-fingerprint detecting app for OPM song title identification
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Author |
Jessica S. Velasco, Gineth Nicole D. Castro, Neil Carlos C. Santos, Samantha Nicole S. Cabrera, Sheena Marie C. Cardinal, Rex Romero and Ryan C. Reyes
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e-ISSN |
1819-6608 |
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On Pages
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1588-1595
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Volume No. |
20
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Issue No. |
18
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Issue Date |
December 30, 2025
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DOI |
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Keywords |
audio-fingerprints, music, python, song identification, spectrogram.
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Abstract
Music has become a part of life, and through this, people can express their thoughts and emotions. OPM, also known as Original Pilipino Music, is an array of songs created and sung by Filipino artists in the Philippines. Through Ubuntu, Python, and VirtualBox, the proponents made an application called EDAmazing, inspired by Shazam and Dejavu’s algorithm and designed to identify song titles through collected audio-fingerprints. They gathered 280 OPM Songs by Filipino bands and solo artists. These songs were randomly selected to ensure the program’s efficiency in identifying, since there are more than three genres of song present. The first test run was done on seven collected audio-fingerprints, and it reached an almost 100% accuracy rate with a 6 out of 7 confidence level. The time of recording used to achieve this accuracy rate is 10 seconds. From the tests done, it can be shown that the program works best in controlled places where there is less noise. Also, the analysis of the EDAmazing is fast when there are fewer songs because of fewer fingerprints, and this was proven by the accumulated group test.
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