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MAŠEK, P. RŮŽIČKA, M.
Original Title
Human-Machine Interface for Mobile Robot Based on an Enhancement Speech Recognition
Type
conference paper
Language
English
Original Abstract
The paper deals with human-machine interface for mobile robot based on enhancement speech recognition system. The speech recognition system can be based on both the various commonly used commercial or open sources. Instead of developing a complete solution from scratch, the third-party system was used. Despite the fact, such solution shows useful results, there are some limitations of uses this kind of speech recognition engine for communication with autonomous robot (e.g. low success rate in recognition of specific words, wrong interpretation in noisy environment, etc.). We present a solution in which the well known Bayesian approach is used for enhance the results and there are described experimental result obtained on autonomous mobile robot in real environment.
Keywords
Speech recognition, Bayesian filter, Probabilistic learning, Human-machine interface, Mobile robot.
Authors
MAŠEK, P.; RŮŽIČKA, M.
RIV year
2014
Released
25. 6. 2014
Publisher
Brno University of Technology, Faculty of Mechanical Engineering, Institute of Automation and Computer Science
Location
Brno, Czech Republic
ISBN
978-80-214-4984-8
Book
MENDEL 2014, 20th International Conference on Soft Computing.
Edition
1
Edition number
1803-3814
Periodical
Mendel Journal series
Year of study
Number
20
State
Czech Republic
Pages from
249
Pages to
252
Pages count
4
BibTex
@inproceedings{BUT108363, author="Petr {Mašek} and Michal {Růžička}", title="Human-Machine Interface for Mobile Robot Based on an Enhancement Speech Recognition", booktitle="MENDEL 2014, 20th International Conference on Soft Computing.", year="2014", series="1", journal="Mendel Journal series", volume="2014", number="20", pages="249--252", publisher="Brno University of Technology, Faculty of Mechanical Engineering, Institute of Automation and Computer Science", address="Brno, Czech Republic", isbn="978-80-214-4984-8", issn="1803-3814" }