Application-Independent and Integration-Friendly Natural Language Understanding

TitleApplication-Independent and Integration-Friendly Natural Language Understanding
Publication TypeConference Paper
Year of Publication2016
AuthorsEppe, M., Trott S., Raghuram V., Feldman J., & Janin A.
Published inProceedings of Global Conference on Artificial Intelligence (GCAI 2016), EPiC Series in Computing
PublisherEasyChair Publications

Natural Language Understanding (NLU) has been a long-standing goal of AI and many related fields, but it is often dismissed as very hard to solve. NLU is required complex flexible systems that take action without further human intervention. This inherently involves strong semantic (meaning) capabilities to parse queries and commands correctly and with high confidence, because an error by a robot or automated vehicle could be disastrous. We describe an implemented general framework, the ECG2 system, that supports the deployment of NLU systems over a wide range of application domains. The framework is based on decades of research on embodied action-oriented semantics and efficient computational realization of a deep semantic analyzer (parser). This makes it linguistically much more flexible, general and reliable than existing shallow approaches that process language without considering its deeper semantics. In this paper we describe our work from a Computer Science perspective of system integration, and show why our particular architecture requires considerably less effort to connect the system to new applications compared to other language processing tools.


This work is supported by the Office of Naval Research grant number N000141110416 and a research grant from Google. Manfred Eppe received support from the German Academic Exchange Service (DAAD) via the FITweltweit program.