Analysis of Importance of the prosodic Features for Automatic Sentence Modality Recognition in French in real Conditions

Pavel Kral 1 Jana Kleckova Christophe Cerisara 1
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper deals with the measure of importance of the prosodic features for automatic sentence modality recognition in French in real conditions. We start by analysing the problem of subjectivity of manual labeling of corpus. Then, we show the results of automatic sentence modality recognition by only two prosodic features: fundamental frequency (F0) and energy. The global accuracy (ACC) is not sufficient for our application: animate a talking head for deaf and hearing-impaired children by information about the sentence type. Next, we analyse the corpus for explaining these results. We consider, that prosodic features are sufficient only for prosodic question detection with accuracy greater than 80 %. For recognition of other modalities with accuracy over 80 %, we need other informations, as language model or semantic.
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Conference papers
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https://hal.inria.fr/inria-00100102
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Submitted on : Tuesday, September 26, 2006 - 10:14:09 AM
Last modification on : Wednesday, September 25, 2019 - 1:16:01 AM

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Pavel Kral, Jana Kleckova, Christophe Cerisara. Analysis of Importance of the prosodic Features for Automatic Sentence Modality Recognition in French in real Conditions. WSEAS International Conference on Electronics, Control and Signal Processing - ICECS'04, Nov 2004, Crete, Greece, pp.1820-1824. ⟨inria-00100102⟩

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