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Application-Independent and Integration-Friendly Natural Language Understanding

13 pagesPublished: September 29, 2016


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.

Keyphrases: Construction Grammar, human-robot interaction, intention recognition, natural language understanding

In: Christoph Benzmüller, Geoff Sutcliffe and Raul Rojas (editors). GCAI 2016. 2nd Global Conference on Artificial Intelligence, vol 41, pages 340--352

BibTeX entry
  author    = {Manfred Eppe and Sean Trott and Vivek Raghuram and Jerome Feldman and Adam Janin},
  title     = {Application-Independent and Integration-Friendly Natural Language Understanding},
  booktitle = {GCAI 2016. 2nd Global Conference on Artificial Intelligence},
  editor    = {Christoph Benzm\textbackslash{}"uller and Geoff Sutcliffe and Raul Rojas},
  series    = {EPiC Series in Computing},
  volume    = {41},
  pages     = {340--352},
  year      = {2016},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2398-7340},
  url       = {},
  doi       = {10.29007/npsn}}
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