ISSD-93 Selected papers presented at the international symposium on Spoken dialogue
The Philips automatic train timetable information system
Speech Communication - Special issue on interactive voice technology for telecommunication applications
Improvising linguistic style: social and affective bases for agent personality
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Verbmobil - Translation of Face-To-Face Dialogs
Grundlagen und Anwendungen der Künstlichen Intelligenz, 17. Fachtagung für Künstliche Intelligenz, Humboldt-Universität zu
Exploring the use of linguistic features in domain and genre classification
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Recognizing text genres with simple metrics using discriminant analysis
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Comparing several aspects of human-computer and human-human dialogues
SIGDIAL '01 Proceedings of the Second SIGdial Workshop on Discourse and Dialogue - Volume 16
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Language users have individual linguistic styles. A spoken dialogue system may benefit from adapting to the linguistic style of a user in input analysis and output generation. To investigate the possibility to automatically classify speakers according to their linguistic style three corpora of spoken dialogues were analyzed. Several numerical parameters were computed for every speaker. These parameters were reduced to linguistically interpretable components by means of a principal component analysis. Classes were established from these components by cluster analysis. Unseen input was classified by trained neural networks with varying error rates depending on corpus type. A first investigation in using special language models for speaker classes was carried out.