Time Recursive Multi-Pitch Estimation Using Group Sparse Recursive Least Squares

Filip Elvander, Johan Swärd, Andreas Jakobsson

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

In this work, we propose a time-recursive multi-pitch estimation algorithm, using a sparse reconstruction framework, assuming
only a few pitches from a large set of candidates to be active at each time instant. The proposed algorithm utilizes a sparse
recursive least squares formulation augmented by an adaptive penalty term specifically designed to enforce a pitch structure on
the solution. When evaluated on a set of ten music pieces, the proposed method is shown to outperform state-of-the-art multi-
pitch estimators in either accuracy or computational spe
Original languageEnglish
Title of host publication50th Asilomar Conference on Signals, Systems, and Computers, 2016
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages369-373
Number of pages5
ISBN (Electronic)978-1-5386-3954-2
DOIs
Publication statusPublished - 2017
Event50th Annual Asilomar Conference on Signals, Systems, and Computers (ASILOMAR 2016) - Asilomar Hotel & Conference Grounds, Pacific Grove, United States
Duration: 2016 Nov 62016 Nov 9

Conference

Conference50th Annual Asilomar Conference on Signals, Systems, and Computers (ASILOMAR 2016)
Country/TerritoryUnited States
CityPacific Grove
Period2016/11/062016/11/09

Subject classification (UKÄ)

  • Probability Theory and Statistics
  • Signal Processing

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