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Capturing and Animating Hand and Finger Motion for 3D Communicative Characters
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In: Wheatland, Nkenge Safiya. (2016). Capturing and Animating Hand and Finger Motion for 3D Communicative Characters. UC Riverside: Computer Science. Retrieved from: http://www.escholarship.org/uc/item/39w9397t (2016)
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Character Modeling through Dialogue for Expressive Natural Language Generation
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Lin, Grace. - : eScholarship, University of California, 2016
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In: Lin, Grace. (2016). Character Modeling through Dialogue for Expressive Natural Language Generation. UC Santa Cruz: Computer Science. Retrieved from: http://www.escholarship.org/uc/item/9c0563w9 (2016)
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Abstract:
Conversation is an essential component of social behavior, one of the primary means by which humans express emotions, moods, attitudes, and personality. Conversation is also critical to storytelling, where key information is often revealed by what a character says, how s/he says it, and how s/he reacts to what other characters say.Interactive narrative systems (INS) are a type of playable media whose applications range from simple entertainment to systems for learning, training, and decision making. Many forms of INS involve interactions with virtual human characters. Thus a key technical capability for such systems is the ability to support natural conversational interaction. While most INS use hand-crafted character dialogue to produce high quality utterances, they suffer from problems of portability and scalability, or what has been called the authoring bottleneck. We believe Natural Language Generation (NLG) is part of the solution to alleviate such burden from authors by automatically generating character dialogue.Here we focus on the issue of character voice. One way to produce believable, dramatic dialogue is to build stylistic models with linguistic features related to NLG decisions. Film/television dialogue are exemplars of many different linguistic styles that were designed to express dramatic characters. Thus we construct a corpus of film/television character dialogue from screenplays and transcripts publicly available from websites such as the Internet Movie Script Database. We apply content analysis and language modeling techniques to extract relevant linguistic features to build character-based stylistic models. We also apply machine learning techniques to discriminate characters base on available metadata such as genre, year, and director.This thesis consists of two parts. The first part involves building a basic character model with film dialogue, and then applying the model to an existing expressive NLG engine to generate different character voices. We then evaluate the generation experiment with a perceptual study, which suggests several natural extensions.The second part involves building a more refined model with television dialogue in order to explore a broader range of stylistic features that can be used to express dramatic characters. We test the model-fit of character models in two ways: 1) ranking experiments to pick out corresponding character’s utterances from a pool of mixed, original characters utterances, and 2) a second generation experiment to test user perceptions of characters.
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Keyword:
Computer science; NLG; NLP
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URL: http://www.escholarship.org/uc/item/9c0563w9 http://n2t.net/ark:/13030/m5n05vgs
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23 |
Exploring and Supporting Today's Collaborative Writing
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Wang, Dakuo. - : eScholarship, University of California, 2016
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In: Wang, Dakuo. (2016). Exploring and Supporting Today's Collaborative Writing. UC Irvine: Information and Computer Science. Retrieved from: http://www.escholarship.org/uc/item/7441493c (2016)
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Artificial Intelligence as a Tool for Understanding Narrative Choices
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In: Mawhorter, Peter Andrew. (2016). Artificial Intelligence as a Tool for Understanding Narrative Choices. UC Santa Cruz: Computer Science. Retrieved from: http://www.escholarship.org/uc/item/1tn22145 (2016)
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25 |
Semantic Interoperability of Multilingual Lexical Resources in Lexical Linked Data ; Interopérabilité Sémantique Multi-lingue des Ressources Lexicales en Données Liées Ouvertes
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In: https://tel.archives-ouvertes.fr/tel-01681358 ; Informatique et langage [cs.CL]. Université Grenoble Alpes, 2016. Français. ⟨NNT : 2016GREAM067⟩ (2016)
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Role of gaze in face-to-face interactions and its analysis among social cues ; Le regard dans les interactions lors d’entretiens en face à face et son analyse parmi les signaux sociaux
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In: https://hal-normandie-univ.archives-ouvertes.fr/tel-02552250 ; Traitement des images [eess.IV]. Normandie Université, 2016. Français (2016)
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Surface Realisation from Knowledge Bases ; Bases de Connaissances et Réalisation de Surface
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In: https://hal.inria.fr/tel-01754499 ; Computation and Language [cs.CL]. Université de Lorraine, 2016. English. ⟨NNT : 2016LORR0004⟩ (2016)
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Questioning scientific texts ; Interroger le texte scientifique
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In: https://tel.archives-ouvertes.fr/tel-01413878 ; Réseaux sociaux et d'information [cs.SI]. Université Toulouse 3 - Paul Sabatier, 2016 (2016)
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RDF Data Interlinking : evaluation of Cross-lingual Methods ; Liage de données RDF : évaluation d'approches interlingues
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In: https://tel.archives-ouvertes.fr/tel-01366030 ; Artificial Intelligence [cs.AI]. Université Grenoble Alpes, 2016. English. ⟨NNT : 2016GREAM011⟩ (2016)
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Semantic Interoperability of Multilingual Lexical Resources as Lexical Linked Data ; Interopérabilité sémantique multilingue des ressources lexicales en données lexicales liées ouvertes
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In: https://tel.archives-ouvertes.fr/tel-01425123 ; Intelligence artificielle [cs.AI]. Université Grenoble Alpes, 2016. Français (2016)
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Textual Inference for Machine Comprehension ; Inférence textuelle pour la compréhension automatique
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In: https://tel.archives-ouvertes.fr/tel-01317577 ; Computation and Language [cs.CL]. Université Paris Saclay (COmUE), 2016. English. ⟨NNT : 2016SACLS004⟩ (2016)
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Effects and handlers in natural language ; Les effects et les handlers dans le langage naturel
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In: https://hal.inria.fr/tel-01417467 ; Computation and Language [cs.CL]. Université de Lorraine, 2016. English. ⟨NNT : 2016LORR0322⟩ (2016)
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Discriminative Training Procedure for Continuous-Space Translation Models ; Apprentissage discriminant des modèles continus en traduction automatique
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In: https://tel.archives-ouvertes.fr/tel-01315755 ; Apprentissage [cs.LG]. Université Paris Saclay (COmUE), 2016. Français. ⟨NNT : 2016SACLS071⟩ (2016)
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French Social Media Mining : Expertise and Sentiment ; Fouille des médias sociaux français : expertise et sentiment
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In: https://hal-lirmm.ccsd.cnrs.fr/tel-01507494 ; Artificial Intelligence [cs.AI]. Université Montpellier, 2016. English. ⟨NNT : 2016MONTT249⟩ (2016)
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Confidence Measures for Alignment and for Machine Translation ; Mesures de Confiance pour l’Alignement et pour la Traduction Automatique
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In: https://tel.archives-ouvertes.fr/tel-01399222 ; Signal and Image Processing. Université Paris Saclay (COmUE), 2016. English. ⟨NNT : 2016SACLS270⟩ (2016)
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Automatic processing of Tunisian dialect: construction of linguistic resources ; TRAITEMENT AUTOMATIQUE DU DIALECTE TUNISIEN : CONSTRUCTION DE RESSOURCES LINGUISTIQUES
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In: https://hal.archives-ouvertes.fr/tel-02869866 ; Informatique et langage [cs.CL]. Université de Sfax (Tunisie), 2016. Français (2016)
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Construction de dictionnaire électronique des verbes du malgache
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In: https://hal.archives-ouvertes.fr/hal-01371850 ; Editions universitaires europeennes, 2016, 978-3-8417-2775-6 ; https://www.editions-ue.com/ (2016)
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Dispositivi formativi e modalità ibride per l’apprendimento linguistico
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In: https://hal.archives-ouvertes.fr/hal-01942392 ; 2016 (2016)
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Named Entities for Computational Linguistics
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In: https://hal-inalco.archives-ouvertes.fr/hal-01359440 ; 2016 (2016)
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Handbook Twitter for Research, 2015 / 2016
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In: https://hal.archives-ouvertes.fr/hal-01257444 ; France. EMLYON Press, 2016, 978-1523263394. ⟨10.5281/zenodo.44882⟩ (2016)
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