@InProceedings{Ranzenberger2021_1119,
author = {Thomas Ranzenberger and Christian Hacker},
booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2021},
title = {VADiMoS: A Web Tool for Designing Voice Assistant Independent and Ontology Based Dialogs},
year = {2021},
editor = {Stefan Hillmann and Benjamin Weiss and Thilo Michael and Sebastian Möller},
month = mar,
pages = {200--207},
publisher = {TUDpress, Dresden},
abstract = {The development of custom skills for the popular Voice Assistants (VAs) of Google and Amazon is usually done in their corresponding eco system for the specific VA. However, the expectations to a voice assistant are very high: natural language understanding, open domain, task oriented, and smart dialogs resulting in correct and context dependent responses. The eco system of the VAs is often not capable to handle such natural dialogs. It is necessary to code simple dialogs running in the backend of the voice assistant, to learn dialogs based on a huge set of domain data, or to design dialogs based on rules. In our approach we design a knowledge graph based on objects and their relations. This knowledge represents the domain, the dialogs, language resources, and rules. A rule engine operates on this dynamic knowledge base and calculates the next dialog step. This approach is voice assistant independent and can be combined with the top on-market VAs, like Alexa or Google Assistant. In this paper we present our web-based Voice Assistant Dialog Modeling Service (VADiMoS) which enables such ontology based dialog modeling, testing, simulation, and deployment to the VA. VADiMoS abstracts the complex definition of dialog rules which are part of our ontology by providing a template-based rule editor. This enables the interactive and test-driven creation of human machine dialogs.},
isbn = {978-3-959082-27-3},
issn = {0940-6832},
keywords = {Postersession 2},
url = {https://www.essv.de/pdf/pdf/2021_200_207.pdf},
}