vol. 7, n. 1-2
pp. 244
ISBN pdf 9791280136770
This special issue on ‘Computational Dialogue Modelling’ discusses recent approaches for modelling pragmatics and common ground in spoken human – human and human– machine interaction. Natural Language Processing (NLP), given the most recent scientific discoveries in the area of intelligent systems and distributed semantics, is now able to build interactive agents whose performance is getting more powerful from year to year. Simple ‘command-based’ models and dialogue state tracking methods are now widely available for very constrained tasks and domains and research in NLP is heading towards the design of more complex scenarios that need to take into account the role of pragmatics in dialogue systems as well as of grounding and commonground.
Hendrik Buschmeier, Faculty of Linguistics and Literary Studies, BielefeldUniversity, Bielefeld,Germany.
Francesco Cutugno, URBAN/ECO ResearchCenter,University of Naples ‘FedericoII’, Naples, Italy.
Maria Di Maro, Interdepartmental Center for Advances in Robotic Surgery.
Antonio Origlia, Department of Electrical Engineering and Information Technologies
Cutugno, Buschmeier, Editorial Note |
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Varonina, Kopp, Knowledge Modelling for Establishment of Common Ground in Dialogue Systems (with debate) |
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Lo Re, Pragmatic approach to construct a multimodal corpus: an Italian pilot corpus |
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Trotta, Guarasci, How are gestures used by politicians? A multimodal co-gesture analysis |
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Sucameli, Lenci, Magnini, Speranza, Simi, Toward Data-Driven Collaborative Dialogue Systems: The JILDA Dataset |
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Salman, Richards, Analysis of Empathic Dialogue in Actual Doctor-Patient Calls and Implications for Design of Embodied Conversational Agents |
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Stranisci, De Leonardis, Bosco, Patti, The Role of Moral Values in the Twitter Debate: a Corpus of Conversations |
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Di Maro, Computational Grounding: An Overview of Common Ground Applications in Conversational Agents |
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Di Maro, Origlia, Cutugno, Cutting melted butter? Common Ground inconsistencies management in dialogue systems using graph databases |
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Dall’Acqua, Tamburini, Towards a linguistically grounded dialog model for chatbot design |
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Joseph, Si, Liaonag, Improving transfer-learning for Data-to-Text Generation via Preserving High-Frequency Phrases and Fact-Checking |
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IJCOL_7_1_11_joseph_et_al | 0,00 € |