Assessment of dialogue systems by means of a new simulation technique
Speech Communication
Towards developing general models of usability with PARADISE
Natural Language Engineering
PARADISE: a framework for evaluating spoken dialogue agents
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Voice and Speech Quality Perception: Assessment and Evaluation (Signals and Communication Technology)
Developing a flexible spoken dialog system using simulation
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Predicting the quality and usability of spoken dialogue services
Speech Communication
User simulation as testing for spoken dialog systems
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
Quality of Telephone-Based Spoken Dialogue Systems
Quality of Telephone-Based Spoken Dialogue Systems
IWSDS'10 Proceedings of the Second international conference on Spoken dialogue systems for ambient environments
Modeling user satisfaction transitions in dialogues from overall ratings
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Advances in the Witchcraft workbench project
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Modeling and predicting quality in spoken human-computer interaction
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
QoE model driven for network services
WWIC'10 Proceedings of the 8th international conference on Wired/Wireless Internet Communications
Towards quality-adaptive spoken dialogue management
SDCTD '12 NAACL-HLT Workshop on Future Directions and Needs in the Spoken Dialog Community: Tools and Data
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Models for predicting judgments about the quality of Spoken Dialog Systems have been used as overall evaluation metric or as optimization functions in adaptive systems. We describe a new approach to such models, using Hidden Markov Models (HMMs). The user's opinion is regarded as a continuous process evolving over time. We present the data collection method and results achieved with the HMM model.