Applying a fuzzy classifier to generate Sp_ToBI annotation: Preliminar results

David Escudero, Lourdes Aguilar, César González, Valentín Cardeñoso, Yurena Gutiérrez

Research output: Book/ReportProceedingResearchpeer-review

5 Citations (Scopus)


One of the goals of the Glissando research project1 is to enrich a radio news corpus [1] with Sp ToBI labels. In this paper we present the application of the automatic predictions of a fuzzy classifier to speed up the labeling process. The strategy is proposed after completing the following steps: a) manual annotation of a part of the Glissando corpus with Sp ToBI labels and checking of the coherence of the labels; b) training of the automatic system; c) validation or correction of the automatic system's predictions by a human expert. The automatic judgments of the classifier are enriched with confidence measures that are useful to represent uncertain situations concerning the label to be assigned. The main aim of the paper is to show that there exists a correspondence between the uncertain situations that are identified during an inter-transcriber experiment and the uncertain situations that the fuzzy classifier detects. Labeling time reduction encourages the use of this strategy.

Original languageAmerican English
Number of pages5
Publication statusPublished - 2014

Publication series

NameProceedings of the International Conference on Speech Prosody
PublisherSpeech Prosody Special Interest Group (SProSIG)
ISSN (Print)2333-2042


  • Fuzzy classifier
  • Prosodic labeling
  • Sp_ToBI


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