HELPR: A Framework to Break the Barrier Across Domains in Spoken Dialog Systems

2016 ◽  
pp. 257-269 ◽  
Author(s):  
Ming Sun ◽  
Yun-Nung Chen ◽  
Alexander I. Rudnicky
Keyword(s):  
Spoken Dialog Systems ◽  
Dialog Systems

scholarly journals Using finite state machines for evaluating spoken dialog systems

2010 ◽  
Author(s):  
Yi Zhu ◽  
Zhaojun Yang ◽  
Helen Meng ◽  
Baichuan Li ◽  
Gina Levow ◽  
...  
Keyword(s):  
Finite State Machines ◽  
State Machines ◽  
Spoken Dialog Systems ◽  
Dialog Systems ◽  
Finite State

Large-scale experiments on data-driven design of commercial spoken dialog systems

2011 ◽  
Author(s):  
D. Suendermann ◽  
J. Liscombe ◽  
J. Bloom ◽  
G. Li ◽  
Roberto Pieraccini
Keyword(s):  
Large Scale ◽  
Data Driven ◽  
Spoken Dialog Systems ◽  
Dialog Systems

Minimally invasive surgery for spoken dialog systems

2010 ◽  
Author(s):  
David Suendermann ◽  
Jackson Liscombe ◽  
Roberto Pieraccini
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Spoken Dialog Systems ◽  
Dialog Systems

Dynamic language modeling using Bayesian networks for spoken dialog systems

2010 ◽  
Author(s):  
Antoine Raux ◽  
Neville Mehta ◽  
Deepak Ramachandran ◽  
Rakesh Gupta
Keyword(s):  
Bayesian Networks ◽  
Language Modeling ◽  
Spoken Dialog Systems ◽  
Dialog Systems ◽  
Dynamic Language

Avatar and Dialog Turn-Yielding Phenomena

2013 ◽  
Vol 9 (2) ◽  
pp. 66-88 ◽  
Author(s):  
Ladislav Kunc ◽  
Zdenek Míkovec ◽  
Pavel Slavík
Keyword(s):  
Discourse Structure ◽  
Conversational Agent ◽  
Correct Judgment ◽  
Spoken Dialog Systems ◽  
Dialog Systems ◽  
Vocal Cues ◽  
Synthesized Speech ◽  
Turn Taking

Turn-taking and turn-yielding phenomena in dialogs receive increasing attention nowadays. A growing number of spoken dialog systems inspire application designers to humanize people’s interaction experience with computers. The knowledge of psychology in discourse structure could be helpful in this effort. In this paper the authors explore effectiveness of selected visual and vocal turn-yielding cues in dialog systems using synthesized speech and an avatar. The aim of this work is to detect the role of visual and vocal cues on dialog turn-change judgment using a conversational agent. The authors compare and study the cues in two experiments. Findings of those experiments suggest that the selected visual turn-yielding cues are more effective than the vocal cues in increasing correct judgment of dialog turn-change. Vocal cues in the experiment show quite poor results and the conclusion discusses possible explanations of that.

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