Multi-Pitch Estimation using NHF with Multi-Dictionary Distinguishing Attack and Reverberation of Sounds

Takanori Fujisawa, Sora Harada, Masaaki Ikehara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a multiple pitch estimation algorithm for the piano music which improves both precision and processing time. The conventional method applies non-negative matrix factorization (NMF) and singular value decomposition to ensure the continuity of sound and pattern of musics. However, audio signal spectrogram has large elements and processing singular value decomposition is inefficient in the computational time. Our method separates the input audio spectrogram into the block of sound. Then we apply a NMF with group sparsity constraint to enforce the continuity of sound. In addition, we use the different dictionaries for the attack part and the reverberation part of the sound. It improves the precision of the estimation for each part.

Original languageEnglish
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1836-1841
Number of pages6
ISBN (Electronic)9781728143002
DOIs
Publication statusPublished - 2019 Nov
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: 2019 Nov 32019 Nov 6

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2019-November
ISSN (Print)1058-6393

Conference

Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
CountryUnited States
CityPacific Grove
Period19/11/319/11/6

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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