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In the domain of music and sound processing, pitch extraction plays a pivotalrole. Our research presents a specialized convolutional neural network designedfor pitch extraction, particularly from the human singing voice in acapellaperformances. Notably, our approach combines synthetic data with auto-labeledacapella sung audio, creating a robust training environment. Evaluation acrossdatasets comprising synthetic sounds, opera recordings, and time-stretchedvowels demonstrates its efficacy. This work paves the way for enhanced pitchextraction in both music and voice settings.

Human Voice Pitch Estimation: A Convolutional Network with Auto-Labeled and Synthetic Data