Comparing CQT and Reassignment Based Chroma Features for Template-based Automatic Chord Recognition

Automatic Chord Recognition (ACR) seeks to extract chords from musical signals. Recently, deep neural network (DNN) approaches have become popular for this task, being employed for feature extraction and sequence modelling. Traditionally, the most important steps in ACR were extraction of chroma features which estimate the energy in each pitch class, and pattern matching using templates or learning-based approaches. In this paper we reconsider chroma features with template matching, employing spectral reassignment chroma with synthetic spectral templates, and find experimental results comparable to those of a recent DNN-based chroma extractor.