Abstract
Natural language processing (NLP) is a well-known and increasingly more important area in human-computer interaction. Talking with a computer in human language is not very far away; for instance, there are automotive systems nowadays where people can control their car by voice, with some limitations. The goal of our research is to develop a natural language framework which will be used to extend existing systems with a natural language controlling capability. Our research focuses on the textual form of input; a proper speech recognizer or speech-to-text converter can produce textual commands and queries anytime. This chapter mainly deals with the optimization of algorithms in the most relevant modules of the framework: POS tagging and function mapping.
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Acknowledgments
The described work was carried out as part of the TÁMOP-4.2.2/B-10/1-2010-0008 project in the framework of the New Hungarian Development Plan. The realization of this project is supported by the European Union, co-financed by the European Social Fund.
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Barabás, P., Kovács, L. (2014). Optimization Tasks in the Conversion of Natural Language Texts into Function Calls. In: Bognár, G., Tóth, T. (eds) Applied Information Science, Engineering and Technology. Topics in Intelligent Engineering and Informatics, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-01919-2_3
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DOI: https://doi.org/10.1007/978-3-319-01919-2_3
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