This project establishes a new research group for dialogue systems (natural-language human-machine communication). This field is booming and the university lacks the related research, teaching, and student involvement.
Research-wise, the project transforms the state-of-the-art in the field by extending the range of possible human-machine dialogues and making them more natural. The use of statistical methods increases system flexibility and reduces development costs.
The main aim of the project is to create a dialogue system capable of natural dialogue in multiple communication domains, including social chit-chat. This system unifies and improves the functions of voice assistants and chatbots. Previously, the former would only react to preset commands, the latter would simulate chit-chat without truly understanding. The system is based on modern machine learning methods, particularly deep neural networks.
The system created in the project will also be deployed for Czech, where the availability of dialogue systems is limited due to high costs of adapting handcrafted rules. The project further aims to develop new, effective methods for automatic dialogue system evaluation.