A HYBRID NEURAL NETWORK BASED ON THE DUPLEX MODEL OF PITCH PERCEPTION FOR SINGING MELODY EXTRACTION

Abstract

In this paper, we build up a hybrid neural network (NN) for singing melody extraction from polyphonic music by imitating human pitch perception. For human hearing, there are two pitch perception models, the spectral model and the temporal model, in accordance with whether harmonics are resolved or not. Here, we first use NNs to implement individual models and evaluate their performance in the task of singing melody extraction. Then, we combine the NNs to constitute the composite NN to simulate the duplex model, which complements the pitch perception from unresolved harmonics of the spectral model using the temporal model. Simulation results show the proposed composite NN outperforms other conventional methods in singing melody extraction.