Jan Schehl


2008

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The Effect of Dialogue System Output Style Variation on Users’ Evaluation Judgments and Input Style
Ivana Kruijff-Korbayová | Ciprian Gerstenberger | Olga Kukina | Jan Schehl
Proceedings of the Fifth International Natural Language Generation Conference

2006

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The SAMMIE System: Multimodal In-Car Dialogue
Tilman Becker | Peter Poller | Jan Schehl | Nate Blaylock | Ciprian Gerstenberger | Ivana Kruijff-Korbayová
Proceedings of the COLING/ACL 2006 Interactive Presentation Sessions

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The SAMMIE Corpus of Multimodal Dialogues with an MP3 Player
Ivana Kruijff-Korbayová | Tilman Becker | Nate Blaylock | Ciprian Gerstenberger | Michael Kaißer | Peter Poller | Verena Rieser | Jan Schehl
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

We describe a corpus of multimodal dialogues with an MP3player collected in Wizard-of-Oz experiments and annotated with a richfeature set at several layers. We are using the Nite XML Toolkit (NXT) to represent and further process the data. We designed an NXTdata model, converted experiment log file data and manualtranscriptions into NXT, and are building tools for additionalannotation using NXT libraries. The annotated corpus will be used to (i) investigate various aspects of multimodal presentation andinteraction strategies both within and across annotation layers; (ii) design an initial policy for reinforcement learning of multimodalclarification requests.

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The SAMMIE Multimodal Dialogue Corpus Meets the Nite XML Toolkit
Ivana Kruijff-Korbayová | Verena Rieser | Ciprian Gerstenberger | Jan Schehl | Tilman Becker
Proceedings of the 5th Workshop on NLP and XML (NLPXML-2006): Multi-Dimensional Markup in Natural Language Processing

2005

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An Experiment Setup for Collecting Data for Adaptive Output Planning in a Multimodal Dialogue System
Ivana Kruijff-Korbayová | Nate Blaylock | Ciprian Gerstenberger | Verena Rieser | Tilman Becker | Michael Kaisser | Peter Poller | Jan Schehl
Proceedings of the Tenth European Workshop on Natural Language Generation (ENLG-05)