An Adaptive Penalty Approach to Multi-Pitch Estimation

Ted Kronvall, Filip Elvander, Stefan Ingi Adalbjörnsson, Andreas Jakobsson

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review

174 Nedladdningar (Pure)


This work treats multi-pitch estimation, and in particular the common misclassification issue wherein the pitch at half of the true fundamental frequency, here referred to as a sub-octave, is chosen instead of the true pitch. Extending on current methods which use an extension of the Group LASSO for pitch estimation, this work introduces an adaptive total variation penalty, which both enforce group- and block sparsity, and deal with errors due to sub-octaves. The method is shown to outperform current state-of-the-art sparse methods, where the model orders are unknown, while also requiring fewer tuning parameters than these. The method is also shown to outperform several conventional pitch estimation methods, even when these are virtued with oracle model orders.
Titel på värdpublikation Signal Processing Conference (EUSIPCO), 2015 23rd European
Antal sidor5
ISBN (elektroniskt)978-0-9928-6263-3
StatusPublished - 2015 dec. 28
Evenemang23rd European Signal Processing Conference, 2015 - Nice, Frankrike
Varaktighet: 2015 aug. 312015 sep. 4
Konferensnummer: 23


NamnEuropean Signal Processing Conference (EUSIPCO)
ISSN (elektroniskt)2076-1465


Konferens23rd European Signal Processing Conference, 2015
Förkortad titelEUSIPCO

Ämnesklassifikation (UKÄ)

  • Sannolikhetsteori och statistik
  • Signalbehandling


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