Voice assistants in vehicles: A case study in mixing traditional linguistic knowledge representations with neural language models
Date:
Voice Assistants in Vehicles has been a popular application of dialogue systems, and there have been many different approaches for this task. This talk will briefly present an evaluation of three models: a domain-specific one based upon typed feature structures, a neural language model, and a mixture of the two, on an unseen but in-domain corpus of user queries in the context of a dialogue classification task. The finding opens the door to a potentially new application of neural language models. The study has changed our perspective on the potential role of structured representations in the future of dialogue systems, and suggests that formal research in this area may have a new role to play in validating and coordinating ad hoc dialogue systems development.