A supervised classification algorithm for note onset detection
EURASIP Journal on Applied Signal Processing
A discriminative model for polyphonic piano transcription
EURASIP Journal on Applied Signal Processing
Document clustering using nonnegative matrix factorization
Information Processing and Management: an International Journal
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In this paper, we propose a musical onset detection method, with reference to polyphonic piano music. The solution proposed consists of an onset detection algorithm based on Short-Time Fourier Transform (STFT) and Non-Negative Matrix Factorization (NMF). This method operates on a frame-by-frame basis and exploits a suitable binary time-frequency representation of the audio signal. To validate this method, we present a collection of experiments using a wide number of musical piano pieces of heterogeneous styles.