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By Yizhao Ni, Matt Mcvicar, Raul Santos-rodriguez and Tijl De Bie


We present a new system, Harmony progression (HP) analyzer, for simultaneous estimation of keys, chords, and bass notes from music audio. It makes use of a novel chromagram of audio that takes perception of loudness into account. Furthermore, it is fully based on machine learning (ML), such that it is potentially applicable to a wider range of genres as long as training data is available. As compared to other models, the proposed system is fast and memory efficient, while achieving state-of-the-art performance. 1. SYSTEM DESCRIPTION 1.1 Loudness based chromagram Let x = [x1,..., xT] be an audio signal with xt indicating the sample data of the t-th frame, then the chromagram extraction assigns attributes (e.g. power or amplitude

Year: 2014
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