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Encouraging Neural Machine Translation to Satisfy Terminology Constraints ...
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Encouraging Neural Machine Translation to Satisfy Terminology Constraints ...
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Sentiment analysis for Urdu online reviews using deep learning models
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In: 38 ; 8 ; 1 (2021)
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Exploiting Tweet Sentiments in Altmetrics Large-Scale Data ...
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Disfluency Insertion for Spontaneous TTS: Formalization and Proof of Concept
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In: SLSP 2018 - 6th International Conference on Statistical Language and Speech Processing ; https://hal.inria.fr/hal-01840798 ; SLSP 2018 - 6th International Conference on Statistical Language and Speech Processing, Oct 2018, Mons, Belgium. pp.1-12, ⟨10.1007/978-3-030-00810-9_4⟩ (2018)
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Identification of research hypotheses and new knowledge from scientific literature ...
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Identification of research hypotheses and new knowledge from scientific literature ...
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Deep context of citations using machine-learning models in scholarly full-text articles
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Pronunciation and disfluency modeling for expressive speech synthesis ; Modélisation de la prononciation et des disfluences pour la synthèse de la parole expressive
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In: https://hal.inria.fr/tel-01668014 ; Artificial Intelligence [cs.AI]. Université Rennes 1, 2017. English. ⟨NNT : 2017REN1S076⟩ (2017)
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Perception of expressivity in TTS: linguistics, phonetics or prosody?
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In: Statistical Language and Speech Processing ; https://hal-univ-lemans.archives-ouvertes.fr/hal-01623916 ; Statistical Language and Speech Processing, Oct 2017, Le Mans, France. pp.262-274, ⟨10.1007/978-3-319-68456-7_22⟩ ; http://grammars.grlmc.com/SLSP2017/index.php (2017)
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Statistical Pronunciation Adaptation for Spontaneous Speech Synthesis
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In: Text, Speech and Dialogue (TSD) ; https://hal.inria.fr/hal-01532035 ; Text, Speech and Dialogue (TSD), Aug 2017, Prague, Czech Republic (2017)
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Adaptation de la prononciation pour la synthèse de la parole spontanée en utilisant des informations linguistiques
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In: Journées d'Études sur la Parole ; https://hal.inria.fr/hal-01321361 ; Journées d'Études sur la Parole, Jul 2016, Paris, France (2016)
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Optimal feature set and minimal training size for pronunciation adaptation in TTS
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In: International Conference on Statistical Language and Speech Processing (SLSP) ; https://hal.inria.fr/hal-01338853 ; International Conference on Statistical Language and Speech Processing (SLSP), Oct 2016, Pilsen, Czech Republic (2016)
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Improving TTS with corpus-specific pronunciation adaptation
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In: Interspeech ; https://hal.inria.fr/hal-01338111 ; Interspeech, Sep 2016, San Francisco, United States (2016)
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Propranolol-induced gingival hyperplasia with Nager syndrome: A rare adverse drug reaction
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Probabilistic Speaker Pronunciation Adaptation for Spontaneous Speech Synthesis Using Linguistic Features
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In: Proceedings of Statistical Language and Speech Processing ; International Conference on Statistical Language and Speech Processing (SLSP) ; https://hal.inria.fr/hal-01181192 ; International Conference on Statistical Language and Speech Processing (SLSP), Nov 2015, Budapest, Hungary. pp.229-241 (2015)
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Phonology Modelling for Expressive Speech Synthesis: a Review
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In: https://hal.inria.fr/hal-01021911 ; [Research Report] PI-2020, IRISA, équipe EXPRESSION. 2014, 18 p., 1 column (2014)
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Meta-knowledge annotation at the event level: comparison between abstracts and full papers
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In: http://www.nactem.ac.uk/papers/Nawaz_BioTxtM_2012.pdf
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