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Titlebook: Natural Language Dialog Systems and Intelligent Assistants; G.G. Lee,H.K. Kim,J.-H. Kim Book 2015 Springer International Publishing Switze

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書目名稱Natural Language Dialog Systems and Intelligent Assistants
編輯G.G. Lee,H.K. Kim,J.-H. Kim
視頻videohttp://file.papertrans.cn/662/661786/661786.mp4
概述Presents implementation of Spoken Dialog Systems and intelligent assistants in everyday applications.Covers tested, scientific successes in language processing and outlines the various applications.Ad
圖書封面Titlebook: Natural Language Dialog Systems and Intelligent Assistants;  G.G. Lee,H.K. Kim,J.-H. Kim Book 2015 Springer International Publishing Switze
描述This book covers state-of-the-art topics on the practical implementation of Spoken Dialog Systems and intelligent assistants in everyday applications. It presents scientific achievements in language processing that result in the development of successful applications and addresses general issues regarding the advances in Spoken Dialog Systems with applications in robotics, knowledge access and communication. Emphasis is placed on the following topics: speaker/language recognition, user modeling / simulation, evaluation of dialog system, multi-modality / emotion recognition from speech, speech data mining, language resource and databases, machine learning for spoken dialog systems and educational and healthcare applications.
出版日期Book 2015
關(guān)鍵詞Cross-lingual Spoken Dialog Systems; Dialogue Management; Emotion Recognition from Speech; Language Rec
版次1
doihttps://doi.org/10.1007/978-3-319-19291-8
isbn_softcover978-3-319-36549-7
isbn_ebook978-3-319-19291-8
copyrightSpringer International Publishing Switzerland 2015
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Rapidly Scaling Dialog Systems with Interactive Learning,earning and then improved in a novel end-to-end visualization tool. We then applied this method to a publicly deployed personal assistant—Microsoft Cortana—where a non-machine learning expert built an intent model in just over 2?h, yielding excellent performance in the commercial service.
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Evaluation of Machine-Led Error Recovery Strategies for Domain Switches in a Spoken Dialog System,in the requested one. A trade-off between list length and confidence has to be made, based on partial interpreted user utterances and correct predictions of follow-up domains. Furthermore, a choice out of two items requires a graphical visualization, whereby a list performs good with an acoustic pre
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