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Conference Papers Year : 2015

Combining lexical and prosodic features for automatic detection of sentence modality in French

Abstract

This article analyzes the automatic detection of sentence modality in French using both prosodic and linguistic information. The goal is to later use such an approach as a support for helping communication with deaf people. Two sentence modalities are evaluated: questions and statements. As linguistic features, we considered the presence of dis-criminative interrogative patterns and two log-likelihood ratios of the sentence being a question rather than a statement: one based on words and the other one based on part-of-speech tags. The prosodic features are based on duration, energy and pitch features estimated over the last prosodic group of the sentence. The evaluations consider using linguistic features stemming from manual transcriptions or from an automatic speech transcription system. The behavior of various sets of features are analyzed and compared. The combination of linguistic and prosodic features gives a slight improvement on automatic transcriptions, where the correct classification performance reaches 72%.
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Dates and versions

hal-01184196 , version 1 (13-08-2015)

Identifiers

  • HAL Id : hal-01184196 , version 1

Cite

Luiza Orosanu, Denis Jouvet. Combining lexical and prosodic features for automatic detection of sentence modality in French. International Conference on Statistical Language and Speech Processing, Nov 2015, Budapest, Hungary. ⟨hal-01184196⟩
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