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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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Abstract:
This paper deals with automatic dialog acts (DAs) recognition in Czech. A Dialog act is defined by J. L. Austin [1] as a meaning of an utterance at the level of illocutionary force. The four following DAs are considered: statements, orders, yes/no questions and other questions. In our previous works, we proposed, implemented and evaluated two new approaches to automatic DAs recognition based on sentence structure. These methods have been validated on a Czech corpus that simulates a task of train tickets reservation. The main goal of this paper is to propose a new approach to solve the problem of lack of training data for automatic DA recognition. This approach clusters the words in the sentence into several groups using maximization of mutual information between two neighbor word classes. The classification accuracy of the unigram model (our baseline approach) is 91 %. The proposed method, a clustered unigram model, reduces the DA error rate by 12 %
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Keyword:
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; dialog act; unigram model; word clustering
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URL: https://hal.archives-ouvertes.fr/hal-00086310/document https://hal.archives-ouvertes.fr/hal-00086310 https://hal.archives-ouvertes.fr/hal-00086310/file/wespacIX.pdf
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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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