Ruofeng Chen

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We present an audio chord recognition system based on a generalization of the Hidden Markov Model (HMM) in which the duration of chords is explicitly considered a type of HMM referred to as a hidden semi-Markov model, or duration-explicit HMM (DHMM). We find that such a system recognizes chords at a level consistent with the state-of-the-art systems –(More)
We propose a novel model for music structural segmentation aiming at combining harmonic and timbral information. We use two-level clustering with splitting initialization and random turbulence to produce segment labels using chroma and MFCC separately as feature. We construct a score matrix to combine segment labels from both aspects. Finally Nonnegative(More)
We present an audio chord recognition system based on a generalization of the Hidden Markov Model (HMM) in which the duration of chords is explicitly considered a type of HMM referred to as a hidden semi-Markov model, or duration-explicit HMM (DHMM). We find that such a system recognizes chords at a level consistent with the state-of-the-art systems –(More)
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