Coffee With a Hint of Data: Towards Using Data-Driven Approaches in Personalised Long-Term Interactions.

ABSTRACT: While earlier research in human-robot interaction pre-dominantly uses rule-based architectures for natural language interaction, these approaches are not flexible enough for long-term interactions in the real world due to the large variation in user utterances. In contrast, data-driven approaches map the user input to the agent output directly, hence, provide more flexibility with these variations without requiring any set of rules. However, data-driven approaches are generally applied to single dialogue exchanges with a user and do not build up a memory over long-term conversation with different users, whereas long-term interactions require remembering users and their preferences incrementally and continuously and recalling previous interactions with users to adapt and personalise the int

SUBMITTER: Irfan B 

PROVIDER: S-EPMC8505524 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature