Chord recognition using Prewitt filter and self-similarity

In this paper we propose a method of audio chord estimation. It does not rely on any machine learning technique, but shows good recognition quality compared to other known algorithms. We calculate a beat-synchronized spectrogram with high time and frequency resolution. It is then processed with an analogue of Prewitt filter used for edge detection in image processing to suppress nonharmonic spectral components. The sequence of chroma vectors obtained from spectrogram is smoothed using selfsimilarity matrix before the actual chord recognition. Chord templates used for recognition are binary-like, but have the tonic and the 5th note accented. The method is evaluated on the 13 Beatles albums. © 2012 Nikolay Glazyrin et al