Skip to Main content Skip to Navigation
Other publications

Transcription of vocal melodies using voice characteristics and algorithm fusion

Christopher Sutton 1 Emmanuel Vincent 1 Mark Plumbley 1 Juan Bello 2
1 Centre for Digital Music
2 Steinhardt School of Culture, Education, and Human Development
Abstract : This paper deals with the transcription of vocal melodies in music recordings. The proposed system relies on two distinct pitch estimators which exploit characteristics of the human singing voice. A Hidden Markov Model (HMM) is used to fuse the pitch estimates and make voicing decisions. The resulting performance is evaluated on the MIREX 2006 Audio Melody Extraction data.
Document type :
Other publications
Complete list of metadatas

Cited literature [6 references]  Display  Hide  Download
https://hal.inria.fr/inria-00544277
Contributor : Emmanuel Vincent <>
Submitted on : Tuesday, December 7, 2010 - 3:50:24 PM
Last modification on : Tuesday, April 14, 2020 - 2:50:12 PM
Document(s) archivé(s) le : Monday, November 5, 2012 - 12:35:25 PM

File

Vignette du document
sutton_MIREX06.pdf
Publisher files allowed on an open archive

Identifiers

  • HAL Id : inria-00544277, version 1

Citation

Christopher Sutton, Emmanuel Vincent, Mark Plumbley, Juan Bello. Transcription of vocal melodies using voice characteristics and algorithm fusion. 2006. ⟨inria-00544277⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

153

Files downloads

444

 

Contact                    Legal Notice                    Personal Data