LifeLine Dialogues with Roberta

Asier López, Ahmed Ratni, Trung Ngo Trong, Javier Mikel Olaso, Seth Montenegro, Minha Lee, Fasih Haider, Stephan Schlögl, Gérard Chollet, Kristiina Jokinen, Dijana Petrovska-Delacrétaz, Hugues Sansen, María Inés Torres

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract / Description of output

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.).
Original languageUndefined/Unknown
Title of host publicationFuture and Emerging Trends in Language Technology. Machine Learning and Big Data
EditorsJosé F Quesada, Francisco-Jesús Martín Mateos, Teresa López Soto
Place of PublicationCham
PublisherSpringer International Publishing AG
Number of pages13
ISBN (Electronic)978-3-319-69365-1
ISBN (Print)978-3-319-69365-1
Publication statusPublished - 29 Oct 2017

Cite this