A Hybrid Neural Network Based on the Duplex Model of Pitch Perception for Singing Melody Extraction

Hsin Chou, Ming Tso Chen, Tai-Shih Chi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

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.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages381-385
Number of pages5
ISBN (Print)9781538646588
DOIs
StatePublished - 10 Sep 2018
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 15 Apr 201820 Apr 2018

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Conference

Conference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period15/04/1820/04/18

Keywords

  • CNN
  • Deep neural network
  • Duplex model
  • Melody extraction
  • Pitch perception

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