Abstract
This paper describes work on dialogue data collection and dialogue system design for personal assistant humanoid robots undertaken at eNTERFACE 2016. The emphasis has been on the system’s speech capabilities and dialogue modeling of what we call LifeLine Dialogues, i.e. dialogues that help people tell stories about their lives. The main goal behind this type of application is to help elderly people exercise their speech and memory capabilities. The system further aims at acquiring a good level of knowledge about the person’s interests and thus is expected to feature open-domain conversations, presenting useful and interesting information to the user. The novel contributions of this work are: (1) a flexible spoken dialogue system that extends the Ravenclaw-type agent-based dialogue management model with topic management and multi-modal capabilities, especially with face recognition technologies, (2) a collection of WOZ-data related to initial encounters and presentation of information to the user, and (3) the establishment of a closer conversational relationship with the user by utilizing additional data (e.g. context, dialogue history, emotions, user goals, etc.).
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Acknowledgments
The authors want to acknowledge the organizers of eNTERFACE 2016 and the University of Twente for providing the opportunity to develop this project. We also want to acknowledge the institutions supporting some of the authors e.g. the Spanish Science Minister under grant TIN2014-54288-C4, ‘ADAPT 13/RC/2106’, and the Academy of Finland project Digital Citizens grant number 270082.
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López, A. et al. (2017). LifeLine Dialogues with Roberta. In: Quesada, J., Martín Mateos , FJ., López Soto, T. (eds) Future and Emerging Trends in Language Technology. Machine Learning and Big Data. FETLT 2016. Lecture Notes in Computer Science(), vol 10341. Springer, Cham. https://doi.org/10.1007/978-3-319-69365-1_6
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DOI: https://doi.org/10.1007/978-3-319-69365-1_6
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