Segmentation in singer turns with the Bayesian Information Criterion

Abstract : As part of a project on indexing ethno-musicological audio recordings, segmentation in singer turns automatically appeared to be essential. In this article, we present the problem of segmentation in singer turns of musical recordings and our first experiments in this direction by exploring a method based on the Bayesian Information Criterion (BIC), which are used in numerous works in audio segmentation, to detect singer turns. The BIC penalty coefficient was shown to vary when determining its value to achieve the best performance for each recording. In order to avoid the decision about which single value is best for all the documents, we propose to combine several segmentations obtained with different values of this parameter. This method consists of taking a posteriori decisions on which segment boundaries are to be kept. A gain of 7.1% in terms of F-measure was obtained compared to a standard coefficient.
Complete list of metadatas

Cited literature [11 references]  Display  Hide  Download
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Monday, July 20, 2015 - 1:35:12 PM
Last modification on : Friday, January 10, 2020 - 9:09:11 PM
Long-term archiving on: Wednesday, October 21, 2015 - 10:49:03 AM


Files produced by the author(s)


  • HAL Id : hal-01178558, version 1
  • OATAO : 13248



Marwa Thlithi, Thomas Pellegrini, Julien Pinquier, Régine André-Obrecht. Segmentation in singer turns with the Bayesian Information Criterion. 15th Annual Conference of International Speech Communication Association (INTERSPEECH 2014), Sep 2014, Singapore, Singapore. pp. 1988-1992. ⟨hal-01178558⟩



Record views


Files downloads