no code implementations • LREC 2022 • Giancarlo Xompero, Michele Mastromattei, Samir Salman, Cristina Giannone, Andrea Favalli, Raniero Romagnoli, Fabio Massimo Zanzotto
In fact, rules from conversational designers used in CLINN significantly outperform a state-of-the-art neural-based dialogue system when trained with smaller sets of annotated dialogues.
no code implementations • 27 Sep 2021 • Giancarlo A. Xompero, Michele Mastromattei, Samir Salman, Cristina Giannone, Andrea Favalli, Raniero Romagnoli, Fabio Massimo Zanzotto
Incorporating explicit domain knowledge into neural-based task-oriented dialogue systems is an effective way to reduce the need of large sets of annotated dialogues.