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Authors: Donghui Feng and Eduard Hovy

Affiliation: Information Sciences Institute, University of Southern California, United States

Abstract: The lack of well-annotated data is always one of the biggest problems for most training-based dialogue systems. Without enough training data, it’s almost impossible for a trainable system to work. In this paper, we explore the evolutionary language understanding approach to build a natural language understanding machine in a virtual human training project. We build the initial training data with a finite state machine. The language understanding system is trained based on the automated data first and is improved as more and more real data come in, which is proved by the experimental results.

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Paper citation in several formats:
Feng, D. and Hovy, E. (2005). MRE: A Study on Evolutionary Language Understanding. In Proceedings of the 2nd International Workshop on Natural Language Understanding and Cognitive Science (ICEIS 2005) - NLUCS; ISBN 972-8865-23-6X, SciTePress, pages 45-54. DOI: 10.5220/0002562300450054

@conference{nlucs05,
author={Donghui Feng. and Eduard Hovy.},
title={MRE: A Study on Evolutionary Language Understanding},
booktitle={Proceedings of the 2nd International Workshop on Natural Language Understanding and Cognitive Science (ICEIS 2005) - NLUCS},
year={2005},
pages={45-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002562300450054},
isbn={972-8865-23-6X},
}

TY - CONF

JO - Proceedings of the 2nd International Workshop on Natural Language Understanding and Cognitive Science (ICEIS 2005) - NLUCS
TI - MRE: A Study on Evolutionary Language Understanding
SN - 972-8865-23-6X
AU - Feng, D.
AU - Hovy, E.
PY - 2005
SP - 45
EP - 54
DO - 10.5220/0002562300450054
PB - SciTePress