Intentional influences on object redescriptions in dialogue: evidence from an empirical study
Intentional influences on object redescriptions in dialogue: evidence from an empirical study
Towards developing general models of usability with PARADISE
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DATE: a dialogue act tagging scheme for evaluation of spoken dialogue systems
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ICCPOL '09 Proceedings of the 22nd International Conference on Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy
Automatic annotation of context and speech acts for dialogue corpora
Natural Language Engineering
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UAHCI '09 Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments
Exploiting discourse structure for spoken dialogue performance analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
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Evalinitiatives '03 Proceedings of the EACL 2003 Workshop on Evaluation Initiatives in Natural Language Processing: are evaluation methods, metrics and resources reusable?
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Proceedings of the 3rd International Universal Communication Symposium
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ALR7 Proceedings of the 7th Workshop on Asian Language Resources
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SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
The Knowledge Engineering Review
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Optimising information presentation for spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
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Computational Linguistics
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Computational Linguistics
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COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony
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This paper describes the application of the PARADISE evaluation framework to the corpus of 662 human-computer dialogues collected in the June 2000 Darpa Communicator data collection. We describe results based on the standard logfile metrics as well as results based on additional qualitative metrics derived using the DATE dialogue act tagging scheme. We show that performance models derived via using the standard metrics can account for 37% of the variance in user satisfaction, and that the addition of DATE metrics improved the models by an absolute 5%.