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Conversational AI for Natural Human-Centric Interaction

12th International Workshop on Spoken Dialogue System Technology, IWSDS 2021, Singapore

Gebonden Engels 2022 9789811955372
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

This book includes peer-reviewed articles from the 12th International Workshop on Spoken Dialogue System Technology, IWSDS 2021, Singapore. Nowadays, dialogue systems or conversational agents have become one of the most important mechanisms for human-computer or human-robot interaction that has been widely adopted as new paradigm for many applications, companies, and final users. On the other hand, recent advances in natural language processing, understanding and generation, as well as a continuous increasing computational power and large number of resources and data, have brought important and consistent improvements to the capabilities of dialogue systems enabling users to have more productive and enjoyable interactions. However, on the threshold of a new decade, the current state of the art shows important areas where improvements are needed such as incorporation of ground-based knowledge, personality, emotions, and adaptability, as well as automatic mechanisms for objective, robust and fast evaluations, especially in the context of developing social and e-health applications. In this 12th edition of the International Workshop on Spoken Dialogue Systems (IWSDS), “Conversational AI for natural human-centric interaction“ compiles and presents a synopsis on current global research efforts to push forward the state of the art in dialogue technologies, including advances to the classical problems of dialogue management, language generation and understanding, personalisation and generation, spokena and multimodal interaction, dialogue evaluation, dialogue modelling and applications, as well as topics related to chatbots and conversational agent technologies.

Specificaties

ISBN13:9789811955372
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer Nature Singapore

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Inhoudsopgave

1. Out-of-Scope Domain and Intent Classification through Hierarchical Joint Modeling,<div>Pengfei Liu, Kun Li and Helen Meng</div><div>2. Segmentation-Based Formulation of Slot Filling Task for Better Generative Modeling,</div><div>Kei Wakabayashi, Johane Takeuchi and Mikio Nakano</div><div>3. Can we predict how challenging Spoken Language Understanding corpora are across sources, languages and domains?</div><div>Frederic Bechet, Christian Raymond, Achraf Hamane, Rim Abrougui, Gabriel Marzinotto and Géraldine Damnati&nbsp;</div><div>Personalisation and Generation</div><div>4. Personalized Extractive Summarization with Discourse Structure Constraints Towards Efficient and Coherent Dialog-based News Delivery,&nbsp;</div><div>Hiroaki Takatsu, Ryota Ando, Hiroshi Honda, Yoichi Matsuyama and Tetsunori Kobayashi</div><div>5. Empathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge,&nbsp;</div><div>Ye Liu, Wolfgang Maier, Wolfgang Minker and Stefan Ultes</div><div>6. Towards Handling Unconstrained User Preferences,</div><div>Suraj Pandey, Svetlana Stoyanchev and Rama Doddipatla</div><div>7. Jurassic is (almost) All You Need: Few-Shot Meaning-to-Text Generation for Open-Domain Dialogue,</div><div>Lena Reed, Cecilia Li, Angela Ramirez, Liren Wu and Marilyn Walker</div><div>Spoken and Multimodal Interaction</div><div>8. Comparison of Automatic Speech Recognition Systems,</div><div>Joshua Kim, Chunfeng Liu, Rafael A. Calvo, Kathryn McCabe, Silas C.R. Taylor, Björn W. Schuller and Kaihang Wu</div><div>9. Multimodal Dialogue Response Timing Estimation Using Dialogue Context Encoder,</div><div>Ryota Yahagi, Yuya Chiba, Takashi Nose and Akinori Ito</div><div>10. Eliciting Cooperative Persuasive Dialogue by Multimodal Emotional Robot,</div><div>Sara Asai, Koichiro Yoshino, Seitaro Shinagawa, Sakriani Sakti and Satoshi Nakamura</div><div>Dialogue Evaluation</div><div>11. Design Guidelines for Developing Systems for Dialogue System Competitions,</div><div>Kazunori Komatani, Ryu Takeda, Keisuke Nakashima, Mikio Nakano&nbsp;</div><div>12. Understanding How People Rate Their Conversations,&nbsp;</div><div>Alexandros Papangelis, Nicole Chartier, Pankaj Rajan, Julia Hirschberg and Dilek Hakkani-Tur</div><div>Dialogue Modelling and Applications</div><div>13. A WoZ Study for an Incremental Proficiency Scoring Interview Agent Eliciting Ratable Samples,</div><div>Mao Saeki, Weronika Demkow, Tetsunori Kobayashi and Yoichi Matsuyama</div>14. SUPPLE: A Dialogue Management Approach based on Conversation Patterns,<div>Florian Kunneman and Koen Hindriks</div><div>15. Dialogue Management as Graph Transformations,</div><div>Nicholas Walker, Torbjørn Dahl and Pierre Lison</div><div>Chatbots and Conversational Agent Technologies</div><div>16. Data Collection for Detecting the Unwillingness to Answer Questions in Dialogue</div><div>Kazumi Nagao, Ryuichiro Higashinaka and Kazuto Ataka</div><div>17. Enhancing Self-Disclosure In Neural Conversation Models By Response Candidate Re-ranking</div><div>Mayank Soni, Benjamin Cowan and Vincent Wade</div><div>18. On the Impact of Self-efficacy on Assessment of User Experience in Customer Service Chatbot Conversations</div><div>Yuexin Cao, Vicente Ivan Sanchez Carmona, Xiaoyi Liu, Changjian Hu, Neslihan Iskender, André Beyer, Sebastian Möller and Tim Polzehl</div><div>19. Learning to ask specific questions naturally in chat-oriented dialogue systems,</div><div>Sota Horiuchi and Ryuichiro Higashinaka</div><div>20. Fine-tuning a pre-trained Transformer-based encoder-decoder model with user-generated question-answer pairs to realize character-like chatbots,</div><div>Koh Mitsuda, Ryuichiro Higashinaka, Hiroaki Sugiyama, Masahiro Mizukami, Tetsuya Kinebuchi, Ryuta Nakamura, Noritake Adachi and Hidetoshi Kawabata</div><div>21. Investigating the Impact of Pre-trained Language Models on Dialog Evaluation,</div><div>Chen Zhang, Luis Fernando D’haro, Thomas Friedrichs, Haizhou Li and Yiming Chen</div><div><br></div>

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        Conversational AI for Natural Human-Centric Interaction