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

Trochlea

正面

Dialogue Management for User-Centered Adaptive Dialoguen. For a proof-of-concept, the resulting dialogue manager is applied in an experiment comparing different confirmation strategies. Having a simple dialogue, the adaptive strategy performs successful and as good as the best strategy.

违反

Situated Interaction in a Multilingual Spoken Information Access Frameworksignals. The robot uses face tracking, nodding and gesturing to support interaction management and the presentation of new information to the partner, while the user speaks, moves, and can touch the robot to interrupt it.

粗语

Investigating Critical Speech Recognition Errors in Spoken Short Messagesnguish between simple and critical errors, where the meaning in the transcript is not the same as the user dictated. We show that our method outperforms standard baseline techniques by 2 % absolute F-score.

Recess

Emotion and Its Triggers in Human Spoken Dialogue: Recognition and Analysise interaction. In this paper, we propose a method of automatic recognition of emotion using support vector machine (SVM) and present further analysis regarding emotion triggers. Experiments were performed on an emotionally colorful dialogue corpus. The result shows performance that surpasses random guessing accuracy.

Magisterial

1860-4862 ic achievements in language processing that have produced su.This book provides a survey of the state-of-the-art in the practical implementation of Spoken Dialog Systems for applications in everyday settings. It includes contributions on key topics in situated dialog interaction from a number of lea

LURE

Book 2016analysis of human discourse and interaction.. The contributions are adapted and expanded contributions from the 2014 International Workshop on Spoken Dialog Systems (IWSDS 2014), where researchers and developers from industry and academia alike met to discuss and compare their implementation experiences, analyses and empirical findings..

GILD

The HRI-CMU Corpus of Situated In-Car Interactionsf the data contained within. The initial analysis indicates that discourse behavior has strong variation across participants, and that general trends relate physical situation and multi-tasking to grounding behavior.

异端邪说2

Evaluating Model that Predicts When People Will Speak to a Humanoid Robot and Handling Variations ofate the relation of how much individual participants feel likely to speak with a model parameter and the instruction given before data collections. Results show that our model can handle the variations.

nascent

Signals and Communication Technologyhttp://image.papertrans.cn/s/image/868080.jpg