Macrosyntactic Segmenters of a French spoken corpus - HAL-SHS - Sciences de l'Homme et de la Société
Conference Papers Year : 2014

Macrosyntactic Segmenters of a French spoken corpus

Ilaine Wang
Sylvain Kahane

Abstract

The aim of this paper is to describe an automated process to segment spoken French transcribed data into macrosyntactic units. While sentences are delimited by punctuation marks for written data, there is no obvious hint nor limit to major units for speech. As a reference, we used the manual annotation of macrosyntactic units based on illocutionary as well as syntactic criteria and developed for the Rhapsodie corpus, a 33.000 words prosodic and syntactic treebank. Our segmenters were built using machine learning methods as supervised classifiers~: segmentation is about identifying the boundaries of units, which amounts to classifying each interword space. We trained six different models on Rhapsodie using different sets of features, including prosodic and morphosyntactic cues, on the assumption that their combination would be relevant for the task. Both types of cues could be resulting either from manual annotation/correction or from fully automated processes, which comparison might help determine the cost of manual effort, especially for the 3M words of spoken French of the Orfeo project those experiments are contributing to.
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Dates and versions

halshs-01004668 , version 1 (11-06-2014)

Identifiers

  • HAL Id : halshs-01004668 , version 1

Cite

Ilaine Wang, Sylvain Kahane, Isabelle Tellier. Macrosyntactic Segmenters of a French spoken corpus. Ninth Language Resources and Evaluation Conference (LREC'14), May 2014, Reykjavík, Iceland. pp.3891-3896. ⟨halshs-01004668⟩
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