Chord Analyzing Based on Signal Processing

The main aim of the presented paper is to create a web portal, which allows the user to reckognize the sequence of chords in the song. To recognize chords from an audio recording, it is necessary to use input signal processing methods such as constant Q-transform or harmonic pitch class profile. A categorization template is created for each supported chord that maximizes the match between the processed signal and the chord. Techniques such as temporal and spectral smoothing or detection of harmonic changes were used for preprocessing. Based on the evaluation methods, the best classification strategy was selected, whose success prediction accuracy reaches 75 percent. Success has been achieved through the use of machine learning techniques. The system is publicly available on the public domain for anyone interested in this type of service.