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Multi-Lingual Dialogue Act Recognition with Deep Learning Methods
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In: Interspeech 2019 ; https://hal.archives-ouvertes.fr/hal-02319818 ; Interspeech 2019, Sep 2019, Graz, Austria. ⟨10.21437/Interspeech.2019-1691⟩ (2019)
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Multi-lingual Dialogue Act Recognition with Deep Learning Methods ...
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On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition
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In: ISSN: 0885-2308 ; EISSN: 1095-8363 ; Computer Speech and Language ; https://hal.archives-ouvertes.fr/hal-01581410 ; Computer Speech and Language, Elsevier, 2018, 47, pp.175 - 193. ⟨10.1016/j.csl.2017.07.009⟩ (2018)
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Deep Neural Networks for Czech Multi-label Document Classification ...
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Investigation of word senses over time using linguistic corpora
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Dialogue act recognition approaches
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In: ISSN: 1335-9150 ; Computing and Informatics ; https://hal.inria.fr/inria-00431396 ; Computing and Informatics, Slovak University Press, Bratislava, 2010, 29 (2), pp.227--250 (2010)
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Lexical Structure for Dialogue Act Recognition
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In: ISSN: 1796-2048 ; Journal of Multimedia ; https://hal.inria.fr/inria-00184475 ; Journal of Multimedia, Academy Publisher, 2007, 2 (3), pp.1-8 (2007)
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Automatic Recognition of Dialogue Acts ; Reconnaissance automatique des actes de dialogue
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In: https://tel.archives-ouvertes.fr/tel-01748248 ; Modeling and Simulation. Université Henri Poincaré - Nancy 1, 2007. English. ⟨NNT : 2007NAN10114⟩ (2007)
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Sentence Modality Recognition In French Based On Prosody ...
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Sentence Modality Recognition In French Based On Prosody ...
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Automatic Recognition of Dialogue Acts ; Reconnaissance automatique des actes de dialogue
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Automatic dialog acts recognition based on sentence structure
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In: IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP/2006 ; https://hal.archives-ouvertes.fr/hal-00078245 ; 2006, pp.61-64 (2006)
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Automatic Dialog Acts Recognition based on Words Clusters
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In: 9th Western Pacific Acoustics Conference - WESPAC IX 2006 ; https://hal.archives-ouvertes.fr/hal-00086310 ; 2006, 6 p (2006)
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Sentence structure for dialog act recognition in Czech
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In: 2nd IEEE International Conference on Information et Communication Technologies: from Theory to Applications - ICTTA´06 ; https://hal.archives-ouvertes.fr/hal-00078247 ; 2006 (2006)
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Combination of classifiers for automatic recognition of dialog acts
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In: Proceedings of the 9th European Conference on Speech Communication and Technology - Interspeech - Eurospeech 2005 - Lisbon, Portugal ; https://hal.archives-ouvertes.fr/hal-00013940 ; 2005, pp.825-828 (2005)
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Analysis of Importance of the prosodic Features for Automatic Sentence Modality Recognition in French in real Conditions
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In: WSEAS International Conference on Electronics, Control and Signal Processing - ICECS'04 ; https://hal.inria.fr/inria-00100102 ; WSEAS International Conference on Electronics, Control and Signal Processing - ICECS'04, Nov 2004, Crete, Greece, pp.1820-1824 (2004)
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Abstract:
Colloque avec actes et comité de lecture. internationale. ; International audience ; 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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Keyword:
[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]; automatic sentences modality recognition (ASMR); corpus modal; énergie; energy; fréquence fondamentale (F0); fundamental frequency (F0); modal corpus; prosodie; prosody; reconnaissance automatique de la modalité des phrases (RAMP)
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URL: https://hal.inria.fr/inria-00100102
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