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A Joint Approach to Extract Multiple Fundamental Frequency in Polyphonic Signals Minimizing Gaussian Spectral Distance

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This paper presents a joint estimation approach to extract multiple fundamental frequency (F0) in monaural polyphonic music signals. In a frame-based analysis, we generate a spectral envelope for each combination of F0 candidates, from non-overlapped partials, under assumption that a harmonic sound is characterized by a Gaussian mixture model (GMM). The optimal F0 candidates combination minimizes a spectral Euclidean distance measure between the original spectrum and Gaussian spectral models. Evaluation was carried out using several piano recordings. Evaluation show promising results.

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