Titlebook: Situated Dialog in Speech-Based Human-Computer Interaction; Alexander Rudnicky,Antoine Raux,Teruhisa Misu Book 2016 Springer International

旁观者

微生物

Construction and Analysis of a Persuasive Dialogue Corpusained some interest in recent dialogue literature. In order to construct more effective persuasive dialogue systems, it is important to understand how the system’s human counterparts perform persuasion. In this paper, we describe the construction of a corpus of persuasive dialogues between real huma

粉笔

Evaluating Model that Predicts When People Will Speak to a Humanoid Robot and Handling Variations ofe examined so that it can be applied to various users. We present two empirical evaluations demonstrating that (1) our proposed model does not depend on the specific participants whose data were used in our previous data collection, and (2) the model can handle variations of individuals and instruct

Ischemia

Entrainment in Pedestrian Direction Giving: How Many Kinds of Entrainment? both lexically and syntactically, by using the same referring expressions or sentence structure. In this paper, we describe a natural language generator .-., which can produce utterances entrained to a range of utterance features used in prior utterances by a human user, and represented in the disc

recession

Situated Interaction in a Multilingual Spoken Information Access Frameworks a speech-based open-domain information access system that enables the user to move around Wikipedia from topic to topic and have chunks of interesting articles read out aloud. The interactions with the robot are situated: they take place in a particular context and are driven according to the user

Hamper

ABIDE

Book 2016t includes contributions on key topics in situated dialog interaction from a number of leading researchers and offers a broad spectrum of perspectives on research and development in the area..In particular, it presents applications in robotics, knowledge access and communication and covers the follo

孤僻

Syntactic Filtering and Content-Based Retrieval of Twitter Sentences for the Generation of System Utertains the valid sentence structure as system utterances, and content-based retrieval ascertains that the content has the relevant information related to user utterances. Experimental results show that our proposed method can appropriately select high-quality Twitter sentences, significantly outperforming the baseline.

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短程旅游