Using Natural Language Processing and discourse Features to Identify Understanding Errors
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Predicting automatic speech recognition performance using prosodic cues
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Gemini: a natural language system for spoken-language understanding
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
ACM Transactions on Computer-Human Interaction (TOCHI)
Learning to predict pitch accents and prosodic boundaries in Dutch
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Classifying recognition results for spoken dialog systems
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
ACM Transactions on Computer-Human Interaction (TOCHI)
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
Proceedings of the 13th international conference on Intelligent user interfaces
Hybrid reinforcement/supervised learning of dialogue policies from fixed data sets
Computational Linguistics
Automatic annotation of context and speech acts for dialogue corpora
Natural Language Engineering
Why is this Wrong? --Diagnosing Erroneous Speech Recognizer Output with a Two Phase Parser
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
User simulations for context-sensitive speech recognition in spoken dialogue systems
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Exploiting discourse structure for spoken dialogue performance analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A Model of Temporally Changing User Behaviors in a Deployed Spoken Dialogue System
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Response-based confidence annotation for spoken dialogue systems
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Spoken language understanding via supervised learning and linguistically motivated features
NLDB'10 Proceedings of the Natural language processing and information systems, and 15th international conference on Applications of natural language to information systems
Introduction to special issue on machine learning for adaptivity in spoken dialogue systems
ACM Transactions on Speech and Language Processing (TSLP)
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We use machine learners trained on a combination of acoustic confidence and pragmatic plausibility features computed from dialogue context to predict the accuracy of incoming n-best recognition hypotheses to a spoken dialogue system. Our best results show a 25% weighted f-score improvement over a baseline system that implements a "grammar-switching" approach to context-sensitive speech recognition.