Multi-pitch estimation via fast group sparse learning

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

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

Abstrakti

In this work, we consider the problem of multi-pitch estimation using sparse heuristics and convex modeling. In general, this is a difficult non-linear optimization problem, as the frequencies belonging to one pitch often overlap the frequencies belonging to other pitches, thereby causing ambiguity between pitches with similar frequency content. The problem is further complicated by the fact that the number of pitches is typically not known. In this work, we propose a sparse modeling framework using a generalized chroma representation in order to remove redundancy and lower the dictionary's block-coherency. The found chroma estimates are then used to solve a small convex problem, whereby spectral smoothness is enforced, resulting in the corresponding pitch estimates. Compared with previously published sparse approaches, the resulting algorithm reduces the computational complexity of each iteration, as well as speeding up the overall convergence.
AlkuperäiskieliEnglanti
Otsikko2016 24th European Signal Processing Conference (EUSIPCO)
KustantajaIEEE
Sivut1093-1097
Sivumäärä5
ISBN (elektroninen)978-0-9928-6265-7
ISBN (painettu)978-1-5090-1891-8
DOI - pysyväislinkit
TilaJulkaistu - 2 syysk. 2016
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaEuropean Signal Processing Conference - Budapest, Unkari
Kesto: 28 elok. 20162 syysk. 2016
Konferenssinumero: 24
http://www.eusipco2016.org/

Julkaisusarja

NimiEuropean Signal Processing Conference
ISSN (painettu)2219-5491
ISSN (elektroninen)2076-1465

Conference

ConferenceEuropean Signal Processing Conference
LyhennettäEUSIPCO
Maa/AlueUnkari
KaupunkiBudapest
Ajanjakso28/08/201602/09/2016
www-osoite

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