Audio Chord Estimation Using Chroma Reduced Spectrogram and Self-similarity
نویسنده
چکیده
In this paper we describe a method of audio chord estimation than does not rely on any machine learning technique. We calculate a beat-synchronized spectrogram with high time and frequency resolution. The sequence of chroma vectors (CRP features based on constant-Q transform) obtained from spectrogram is smoothed using self-similarity matrix before the actual chord recognition. Binary chord templates with 3 harmonics are used. Two heuristics are applied to the resulting chord sequence to reduce the number of major-minor chord confusions and to remove singlebeat chords. The method is evaluated on the Isophonics [7] and RWC Popular Music [5] datasets (318 tracks in total).
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