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

Luiza Orosanu 1 Denis Jouvet 1
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
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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https://hal.inria.fr/hal-01184196
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Submitted on : Thursday, August 13, 2015 - 11:29:07 AM
Last modification on : Thursday, March 5, 2020 - 4:51:12 PM
Long-term archiving on: : Saturday, November 14, 2015 - 10:15:58 AM

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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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