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Backchannel Behavior Influences the Perceived Personality of Human and Artificial Communication Partners
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TurnGPT : a Transformer-based Language Model for Predicting Turn-taking in Spoken Dialog
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TurnGPT: a Transformer-based Language Model for Predicting Turn-taking in Spoken Dialog ...
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KTH Tangrams: A Dataset for Research on Alignment and Conceptual Pacts in Task-Oriented Dialogue
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Fundamental frequency accommodation in multi-party human-robot game interactions : The effect of winning or losing
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Skantze, Gabriel; Ibrahim, Omnia; Dellwo, Volker; Stoll, Sabine. - : KTH, Tal, musik och hörsel, TMH, 2019. : URPP Language and Space, University of Zurich, Switzerland, 2019. : Department of comparative linguistics, University of Zurich, Switzerland, 2019. : Department of computational linguistics, University of Zurich, Switzerland, 2019
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Abstract:
In human-human interactions, the situational context plays a large role in the degree of speakers’ accommodation. In this paper, we investigate whether the degree of accommodation in a human-robot computer game is affected by (a) the duration of the interaction and (b) the success of the players in the game. 30 teams of two players played two card games with a conversational robot in which they had to find a correct order of five cards. After game 1, the players received the result of the game on a success scale from 1 (lowest success) to 5 (highest). Speakers’ fo accommodation was measured as the Euclidean distance between the human speakers and each human and the robot. Results revealed that (a) the duration of the game had no influence on the degree of fo accommodation and (b) the result of Game 1 correlated with the degree of fo accommodation in Game 2 (higher success equals lower Euclidean distance). We argue that game success is most likely considered as a sign of the success of players’ cooperation during the discussion, which leads to a higher accommodation behavior in speech. ; QC 20200214
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Keyword:
Language Technology (Computational Linguistics); Språkteknologi (språkvetenskaplig databehandling)
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URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-267215
https://doi.org/10.21437/Interspeech.2019-2496
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Multimodal Continuous Turn-Taking Prediction Using Multiscale RNNs ...
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A Multimodal Corpus for Mutual Gaze and Joint Attention in Multiparty Situated Interaction
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Kontogiorgos, Dimosthenis; Avramova, Vanya; Alexanderson, Simon. - : KTH, Tal, musik och hörsel, TMH, 2018. : KTH, 2018. : Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland, 2018. : Paris, 2018
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Towards a General, Continuous Model of Turn-taking in Spoken Dialogue using LSTM Recurrent Neural Networks
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Skantze, Gabriel. - : KTH, Tal-kommunikation, 2017. : Saarbrucken, Germany, 2017
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| 14 |
Tutoring Robots
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In: IFIP Advances in Information and Communication Technology ; 9th International Summer Workshop on Multimodal Interfaces (eNTERFACE) ; https://hal.inria.fr/hal-01350740 ; 9th International Summer Workshop on Multimodal Interfaces (eNTERFACE), Jul 2013, Lisbon, Portugal. pp.80-113, ⟨10.1007/978-3-642-55143-7_4⟩ (2013)
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Error Handling in Spoken Dialogue Systems : Managing Uncertainty, Grounding and Miscommunication
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Skantze, Gabriel. - : KTH, Tal, musik och hörsel, TMH, 2007. : Stockholm : KTH, 2007
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