ADVISER: A Dialog System Framework for Education & Research

Autor: Daniel Ortega, Maximilian Schmidt, Ngoc Thang Vu, Dirk Väth, Zorica Karacevic, Moritz Völkel, Gianna Weber, Lindsey Vanderlyn
Rok vydání: 2019
Předmět:
Zdroj: ACL (3)
DOI: 10.18653/v1/p19-3016
Popis: In this paper, we present ADVISER - an open source dialog system framework for education and research purposes. This system supports multi-domain task-oriented conversations in two languages. It additionally provides a flexible architecture in which modules can be arbitrarily combined or exchanged - allowing for easy switching between rules-based and neural network based implementations. Furthermore, ADVISER offers a transparent, user-friendly framework designed for interdisciplinary collaboration: from a flexible back end, allowing easy integration of new features, to an intuitive graphical user interface supporting nontechnical users.
Databáze: OpenAIRE