Revisiting Input Time-frequency Representations in Multi-pitch Estimation for Vocal Ensembles

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Revisiting Input Time-frequency Representations in Multi-pitch Estimation for Vocal Ensembles

Multi-pitch estimation in vocal ensembles is challenging because singers occupy overlapping pitch ranges and often sing at closely spaced fundamental frequencies, causing their harmonics to overlap in time-frequency representations. Existing models commonly use harmonic constant-Q transform (HCQT)-based representations to provide frequency-adaptive resolution, at the cost of expensive feature extraction when training mixtures are generated on the fly. We revisit this design and compare HCQT with

Source: ArXiv AI