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Titlebook: Conversational AI for Natural Human-Centric Interaction; 12th International W Svetlana Stoyanchev,Stefan Ultes,Haizhou Li Conference procee

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书目名称Conversational AI for Natural Human-Centric Interaction
副标题12th International W
编辑Svetlana Stoyanchev,Stefan Ultes,Haizhou Li
视频videohttp://file.papertrans.cn/238/237781/237781.mp4
概述Includes articles from the 12th International Workshop on Spoken Dialogue System Technology, IWSDS 2021, Singapore.Compiles and presents a synopsis on current global research efforts.Highlights proble
丛书名称Lecture Notes in Electrical Engineering
图书封面Titlebook: Conversational AI for Natural Human-Centric Interaction; 12th International W Svetlana Stoyanchev,Stefan Ultes,Haizhou Li Conference procee
描述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, robustand 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 A
出版日期Conference proceedings 2022
关键词Speech processing; Dialogue processing; Human-centric interaction; Spoken dialogue system; Conversationa
版次1
doihttps://doi.org/10.1007/978-981-19-5538-9
isbn_softcover978-981-19-5540-2
isbn_ebook978-981-19-5538-9Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Verilog: Frequently Asked Questionsyed vocal assistant with different distributional properties. We show that the predictor can highlight challenging utterances and explain the main complexity factors even though this corpus was collected in a completely different setting.
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Patrizia Bagnarelli,Massimo Clementiiments with dialogue acts for video games show that with 10-shot prompting, both models learn to control dialogue acts, but Athena-Jurassic has significantly higher coherence and only 4% untrue hallucinations. Our results suggest that Athena-Jurassic produces high enough quality outputs to be useful
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Conversational AI for Natural Human-Centric Interaction12th International W
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Out-of-Scope Domain and Intent Classification through Hierarchical Joint Modelingarchical model that learns the intent and domain representations in the higher and lower layers respectively. Experiments show that the model outperforms existing methods in terms of accuracy, out-of-scope recall, and .. Additionally, threshold-based post-processing further improves performance by b
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Jurassic is (Almost) All You Need: Few-Shot Meaning-to-Text Generation for Open-Domain Dialogueiments with dialogue acts for video games show that with 10-shot prompting, both models learn to control dialogue acts, but Athena-Jurassic has significantly higher coherence and only 4% untrue hallucinations. Our results suggest that Athena-Jurassic produces high enough quality outputs to be useful
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