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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 Hits 1 – 20 of 104 1 Computational models of disfluencies : fillers and discourse markers in spoken language understanding ; Modèles computationnels des disfluences dans le traitement de la parole Dinkar, Tanvi. - : HAL CCSD, 2022 In: https://tel.archives-ouvertes.fr/tel-03653211 ; Computer science. Institut Polytechnique de Paris, 2022. English. ⟨NNT : 2022IPPAT001⟩ (2022) BASE Show details 2 Affirming and Denying the Hybrid Character of Robots: Literary Investigations ... Li, Yue. - : Technology and Language, 3(1), 136-146, 2022 BASE Show details 3 Is a Wizard-of-Oz Required for Robot-Led Conversation Practice in a Second Language? Águas Lopes, José David; Cumbal, Ronald; Engwall, Olov. - : KTH, Tal-kommunikation, 2022. : KTH, Tal, musik och hörsel, TMH, 2022. : Springer Nature, 2022 BASE Show details 4 Affect-enhancing speech characteristics - the influence of verbal and prosodic components ... Klüber, Kim. - : Open Science Framework, 2022 BASE Show details 5 Affect-enhancing speech characteristics ... Klüber, Kim. - : Open Science Framework, 2022 BASE Show details 6 "It Is Not the Robot Who Learns, It Is Me." Treating Severe Dysgraphia Using Child-Robot Interaction Gargot, Thomas; Asselborn, Thibault; Zammouri, Ingrid... In: ISSN: 1664-0640 ; Frontiers in Psychiatry ; https://hal.sorbonne-universite.fr/hal-03152170 ; Frontiers in Psychiatry, Frontiers, 2021, 12, pp.596055. ⟨10.3389/fpsyt.2021.596055⟩ (2021) BASE Show details 7 Does the Goal Matter? Emotion Recognition Tasks Can Change the Social Value of Facial Mimicry towards Artificial Agents Perugia, Giulia; Paetzel-Prüssman, Maike; Hupont, Isabelle... In: ISSN: 2296-9144 ; Frontiers in Robotics and AI ; https://hal.archives-ouvertes.fr/hal-03409678 ; Frontiers in Robotics and AI, Frontiers Media S.A., 2021, 8, ⟨10.3389/frobt.2021.699090⟩ (2021) BASE Show details 8 Grounded Language Learning: Where Robotics and NLP Meet ... Matuszek, Cynthia. - : IJCAI, 2021 BASE Show details 9 Towards Making Virtual Human-Robot Interaction a Reality ... Higgins, Padraig; Kebe, Gaoussou Youssouf; Berlier, Adam. - : Association for Computing Machinery, 2021 BASE Show details 10 A Novel Speech to Mouth Articulation System for Realistic Humanoid Robots Strathearn, Carl; Minhua, Ma. - : Springer, 2021 BASE Show details 11 Organising in the Industry 4.0: the rise of the "Empathetic Union" ... Languaging Diversity 2021 2021; Ortu, Claudia. - : Underline Science Inc., 2021 BASE Show details 12 Attribution of Autonomy and its Role in Robotic Language Acquisition Althoefer, Kaspar; Foerster, Frank. - 2021 Abstract: © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. ; The false attribution of autonomy and related concepts to artificial agents that lack the attributed levels of the respective characteristic is problematic in many ways. In this article we contrast this view with a positive viewpoint that emphasizes the potential role of such false attributions in the context of robotic language acquisition. By adding emotional displays and congruent body behaviors to a child-like humanoid robot’s behavioral repertoire we were able to bring naïve human tutors to engage in so called intent interpretations. In developmental psychology, intent interpretations can be hypothesized to play a central role in the acquisition of emotion, volition, and similar autonomy-related words. The aforementioned experiments originally targeted the acquisition of linguistic negation. However, participants produced other affect- and motivation-related words with high frequencies too and, as a consequence, these entered the robot’s active vocabulary. We will analyze participants’ non-negative emotional and volitional speech and contrast it with participants’ speech in a non-affective baseline scenario. Implications of these findings for robotic language acquisition in particular and artificial intelligence and robotics more generally will also be discussed. ; Peer reviewed ; Final Published version Keyword: attribution of agency; attribution of autonomy; Human-Robot Interaction; language acquisition URL: http://hdl.handle.net/2299/24008 BASE Hide details 13 Attribution of Autonomy and its Role in Robotic Language Acquisition Foerster, Frank; Althoefer, Kaspar. - 2021 BASE Show details 14 Dynamic Generation of Spatial Referring Expressions for Social Robots Wallbridge, Christopher. - : University of Plymouth, 2021 BASE Show details 15 Interaction and collaboration in robot-assisted language learning for adults Engwall, Olov; David Lopes, José. - : KTH, Tal, musik och hörsel, TMH, 2020. : Interaction Lab, Heriot-Watt University, Edinburgh, UK, 2020 BASE Show details 16 Identification of Speech Characteristics to Distinguish Human Personality of Introversive and Extroversive Male Groups Park; Lee; Brotherton... In: International Journal of Environmental Research and Public Health ; Volume 17 ; Issue 6 (2020) BASE Show details 17 Robot-Mediated interviews: A field trial with a potential real-world user Wood, Luke; Dautenhahn, Kerstin; Rainer, Austen. - 2020 BASE Show details 18 Robot-Mediated interviews: A field trial with a potential real-world user Wood, Luke; Dautenhahn, Kerstin; Rainer, Austen. - 2020 BASE Show details 19 Robot-Mediated interviews: A field trial with a potential real-world user Wood, Luke; Dautenhahn, Kerstin; Rainer, Austen. - 2020 BASE Show details 20 How are you? How a Robot can Learn to Express its own Roboceptions Trifirò, Irene; Augello, Agnese; Maniscalco, Umberto. - 2020 BASE Show details Page: 1 2 3 4 5 6

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