Auswahl der wissenschaftlichen Literatur zum Thema „Robots conversationnels“
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Zeitschriftenartikel zum Thema "Robots conversationnels"
Borderieux, Julien. „Agent conversationnel et pragmatique gricéenne“. SHS Web of Conferences 191 (2024): 01001. http://dx.doi.org/10.1051/shsconf/202419101001.
Der volle Inhalt der QuelleLe Corf, Jean-Baptiste. „L’organisation homme-machine de la communication automatisée d’entreprise dans le capitalisme : le cas des robots conversationnels“. Communication & management 14, Nr. 2 (2017): 35. http://dx.doi.org/10.3917/comma.142.0035.
Der volle Inhalt der QuelleTisseron, Serge. „Cinq concepts fondamentaux de la cyberpsychologie“. psychologie clinique, Nr. 49 (2020): 7–15. http://dx.doi.org/10.1051/psyc/202049007.
Der volle Inhalt der QuelleNicolay, S., P. Nardone, E. Civade und C. Laborde. „Évaluation de l’adhésion et de la satisfaction de Max®, un robot conversationnel pour les patients, dans la réalisation de la conciliation médicamenteuse d’entrée proactive“. Le Pharmacien Clinicien 57, Nr. 4 (Dezember 2022): e28. http://dx.doi.org/10.1016/j.phacli.2022.10.412.
Der volle Inhalt der QuelleQuinio, Bernard, und Marc Bidan. „ChatGPT : Un robot conversationnel peut-il enseigner ?“ Management & Data Science, 2023. http://dx.doi.org/10.36863/mds.a.22060.
Der volle Inhalt der QuelleKerinska, Nikoleta. „Agents intelligents oeuvres d’art“. Revista Farol 18, Nr. 27 (22.09.2023). http://dx.doi.org/10.47456/rf.v18i27.42482.
Der volle Inhalt der QuelleDissertationen zum Thema "Robots conversationnels"
Schrive, Etienne. „Étude et réalisation d'un système de conception assistée par ordinateur pour la robotique : application à la programmation graphique des robots de type SCARA“. Montpellier 2, 1988. http://www.theses.fr/1988MON20142.
Der volle Inhalt der QuelleChevet, Clotilde. „"L'interaction homme-machine" : un système d'écritures qui fait monde“. Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUL170.
Der volle Inhalt der QuelleThis thesis aims to study “personal assistants”, these “textual beings” split between computer code and natural language, between writing and orality. In light of Apple's promise to its users, "Talk to Siri as a person", our research explores the writing system within which human-machine communicational mimesis takes shape. We study different facets of this system: its (human and machinic) enunciations, its gestures (mobilising both the hand and the voice) and its actors (backstage as in the spotlight). At the crossroads of information and communication sciences and anthropology, this thesis combines various approaches: epistemological investigation, media archaeology and online ethnography. We explore three issues of writing in "human-machine interaction": the relationship to oneself as it allows personal expression, the relationship to the Other since it enables communication, and finally the relationship to the world since it enables it to be said and organized
Bertel, François. „Animation d'humanoi͏̈de dans un contexte conversationnel impliquant un dialogue verbal et non verbal“. Rennes 1, 2003. http://www.theses.fr/2003REN10090.
Der volle Inhalt der QuelleDutrey, Camille. „Analyse et détection automatique de disfluences dans la parole spontanée conversationnelle“. Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112415/document.
Der volle Inhalt der QuelleExtracting information from linguistic data has gain more and more attention in the last decades inrelation with the increasing amount of information that has to be processed on a daily basis in the world. Since the 90’s, this interest for information extraction has converged to the development of researches on speech data. In fact, speech data involves extra problems to those encountered on written data. In particular, due to many phenomena specific to human speech (e.g. hesitations, corrections, etc.). But also, because automatic speech recognition systems applied on speech signal potentially generates errors. Thus, extracting information from audio data requires to extract information by taking into account the "noise" inherent to audio data and output of automatic systems. Thus, extracting information from speech data cannot be as simple as a combination of methods that have proven themselves to solve the extraction information task on written data. It comes that, the use of technics dedicated for speech/audio data processing is mandatory, and epsecially technics which take into account the specificites of such data in relation with the corresponding signal and transcriptions (manual and automatic). This problem has given birth to a new area of research and raised new scientific challenges related to the management of the variability of speech and its spontaneous modes of expressions. Furthermore, robust analysis of phone conversations is subject to a large number of works this thesis is in the continuity.More specifically, this thesis focuses on edit disfluencies analysis and their realisation in conversational data from EDF call centres, using speech signal and both manual and automatic transcriptions. This work is linked to numerous domains, from robust analysis of speech data to analysis and management of aspects related to speech expression. The aim of the thesis is to propose appropriate methods to deal with speech data to improve text mining analyses of speech transcriptions (treatment of disfluencies). To address these issues, we have finely analysed the characteristic phenomena and behavior of spontaneous speech (disfluencies) in conversational data from EDF call centres and developed an automatic method for their detection using linguistic, prosodic, discursive and para-linguistic features.The contributions of this thesis are structured in three areas of research. First, we proposed a specification of call centre conversations from the prespective of the spontaneous speech and from the phenomena that specify it. Second, we developed (i) an enrichment chain and effective processings of speech data on several levels of analysis (linguistic, acoustic-prosodic, discursive and para-linguistic) ; (ii) an system which detect automaticcaly the edit disfluencies suitable for conversational data and based on the speech signal and transcriptions (manual or automatic). Third, from a "resource" point of view, we produced a corpus of automatic transcriptions of conversations taken from call centres which has been annotated in edition disfluencies (using a semi-automatic method)
Mondou, Damien. „Gestion adaptative des contenus numériques : proposition d’un framework générique par apprentissage et re-scénarisation dynamique“. Thesis, La Rochelle, 2019. http://www.theses.fr/2019LAROS029.
Der volle Inhalt der QuelleThis thesis aims to propose an architecture that addresses the design, supervision, management and adaptation of an interactive experience. We therefore propose a complete framework to facilitate the modeling phase of an interactive system and guarantee sufficient flexibility to achieve the objectives of complexity, scalability, adaptability and improvement through automatic learning. For this purpose, the formal model, CIT, based on two layers of description was introduced. The dynamic supervision process consists in controlling the interactive experience with regard to the formal model, based on networks of timed input/output automata. Two softwares, CELTIC (Common Editor for Location Time Interaction and Content) and EDAIN (Execution Driver based on Artificial INtelligence), implementing the CIT model and the activity supervision engine respectively, were developed during this thesis
Gerval, Jean-Pierre. „Contribution à l'étude des systèmes coopératifs en robotique : LCOOP, Un langage de coopération“. Valenciennes, 1987. https://ged.uphf.fr/nuxeo/site/esupversions/7c703658-6f55-4040-a7a2-bddc0be6e627.
Der volle Inhalt der QuelleBiancardi, Béatrice. „Les premières secondes comptent : gérer les premières impressions pour un agent virtuel plus engageant“. Electronic Thesis or Diss., Sorbonne université, 2019. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2019SORUS037.pdf.
Der volle Inhalt der QuelleThe first moments of an interaction with a virtual character are critical since users form impressions about them, which can affect the rest of the interaction, in terms of engagement and willingness to continue it. In this Thesis we present a computational model for managing user’s impression of agent’s warmth and competence (W&C), the 2 fundamentals dimensions of social cognition. The goal of the agent is to adapt its non-verbal behaviour in real-time during an interaction, according to user’s non-verbal reactions. Our approach starts from the analysis of a corpus of human-human interactions in order to identify a set of non-verbal behaviours eliciting different degrees of W&C. A perceptual study then investigated how these behaviours are perceived when performed by a virtual agent. A reinforcement learning (RL) algorithm has been developed to allow the agent to learn in real-time the behaviours which give the best impression to the user, according to its goal. User’s non-verbal reactions (computed from low-level signals such as facial action units) are used as a reward for the RL. We have personalized the computational model in order to adapt the agent’s behaviours with the goal of maximizing user’s engagement or impressions of agent’s W&C. Two use cases have been run in order to evaluate the impact of an adapting agent on user’s impressions and perception of the interaction, compared to a non-adapting agent. In the first experiment the agent adapted its self-presentational strategies in order to maximise user’s engagement. In the second one the agent learned the best combinations of non-verbal behaviours to display in order to maximise user’s impressions of its W&C
Lathuiliere, Stéphane. „Modèles profonds de régression et applications à la vision par ordinateur pour l'interaction homme-robot“. Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM026/document.
Der volle Inhalt der QuelleIn order to interact with humans, robots need to perform basic perception taskssuch as face detection, human pose estimation or speech recognition. However, in order have a natural interaction with humans, the robot needs to modelhigh level concepts such as speech turns, focus of attention or interactions between participants in a conversation. In this manuscript, we follow a top-downapproach. On the one hand, we present two high-level methods that model collective human behaviors. We propose a model able to recognize activities thatare performed by different groups of people jointly, such as queueing, talking.Our approach handles the general case where several group activities can occur simultaneously and in sequence. On the other hand, we introduce a novelneural network-based reinforcement learning approach for robot gaze control.Our approach enables a robot to learn and adapt its gaze control strategy inthe context of human-robot interaction. The robot is able to learn to focus itsattention on groups of people from its own audio-visual experiences.Second, we study in detail deep learning approaches for regression prob-lems. Regression problems are crucial in the context of human-robot interaction in order to obtain reliable information about head and body poses or theage of the persons facing the robot. Consequently, these contributions are really general and can be applied in many different contexts. First, we proposeto couple a Gaussian mixture of linear inverse regressions with a convolutionalneural network. Second, we introduce a Gaussian-uniform mixture model inorder to make the training algorithm more robust to noisy annotations. Finally,we perform a large-scale study to measure the impact of several architecturechoices and extract practical recommendations when using deep learning approaches in regression tasks. For each of these contributions, a strong experimental validation has been performed with real-time experiments on the NAOrobot or on large and diverse data-sets