Statistical and Empirical Approaches for Spoken Dialogue Systems
Papers from the AAAI Workshop
Pascal Poupart, Stephanie Seneff, Jason Williams, and Steve Young, Cochairs
Technical Report WS-06-14
56 pp., $30.00
ISBN 978-1-57735-296-9
[Add to Cart] [View Cart]
This workshop seeks to draw new work on statistical and empirical approaches for spoken dialogue systems. Both theoretical and applied work was welcomed, addressing issues such as:
- Representations and data structures suitable for automated learning of dialogue models
- Machine learning techniques for automatic generation and improvement of dialogue managers
- Machine learning techniques for ontology construction and integration
- Techniques to accurately simulate human-computer dialogue
- Creation, use, and evaluation of user models
- Methods for automatic evaluation of dialogue systems
- Integration of spoken dialogue systems into larger intelligent agents, such as robots
- Investigations into appropriate optimization criteria for spoken dialogue systems
- Applications and real-world examples of spoken dialogue systems incorporating statistical or empirical techniques
- Use of statistical or empirical techniques within multi-modal dialogue systems
- Application of statistical or empirical techniques to multi-lingual spoken dialogue systems
- Rapid development of spoken dialogue systems from database content and corpora
- Adaptation of dialogue systems to new domains and languages
- The use and application of techniques and methods from related areas, such as cognitive science, operations research, emergence models, etc.
- Any other aspect of the application of statistical or empirical techniques to Spoken Dialogue Systems.