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» Learning User Intentions in Spoken Dialogue Systems
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ACL
2010
14 years 8 months ago
The Impact of Interpretation Problems on Tutorial Dialogue
Supporting natural language input may improve learning in intelligent tutoring systems. However, interpretation errors are unavoidable and require an effective recovery policy. We...
Myroslava Dzikovska, Johanna D. Moore, Natalie B. ...
JUCS
2006
185views more  JUCS 2006»
14 years 10 months ago
The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States
We outline the Berlin Brain-Computer Interface (BBCI), a system which enables us to translate brain signals from movements or movement intentions into control commands. The main co...
Benjamin Blankertz, Guido Dornhege, Steven Lemm, M...
AIA
2007
14 years 11 months ago
Improving extractive dialogue summarization by utilizing human feedback
Automatic summarization systems usually are trained and evaluated in a particular domain with fixed data sets. When such a system is to be applied to slightly different input, la...
Margot Mieskes, Christoph Müller, Michael Str...
ECTEL
2010
Springer
14 years 11 months ago
Content, Social, and Metacognitive Statements: An Empirical Study Comparing Human-Human and Human-Computer Tutorial Dialogue
Abstract. We present a study which compares human-human computermediated tutoring with two computer tutoring systems based on the same materials but differing in the type of feedba...
Myroslava Dzikovska, Natalie B. Steinhauser, Johan...
ER
2008
Springer
179views Database» more  ER 2008»
14 years 11 months ago
Recommendation Based Process Modeling Support: Method and User Experience
Abstract Although most workflow management systems nowadays offer graphical editors for process modeling, the learning curve is still too steep for users who are unexperienced in p...
Thomas Hornung, Agnes Koschmider, Georg Lausen