Abstract
Ordered Weighted Average is a class of aggregators that generalize the concepts of median, minimum and maximum. An important feature of these aggregators is that they can be readily implemented in hardware. In our work we study whether these aggregators can be advantageously used to aggregate decisions by the group of experts. The experts in question are fuzzy logic recognition structures, a kind of a neural network. This paper compares the efficiency of group decision against the best trained system (within a class of fuzzy logic functions) on instances of two vowel discrimination problem.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bishop, C.M.: Pattern Recognition and Machine Learning. Springer (2006) ISBN 0-387-31073-8
Flanagan, J.L., Allen, J.B., Hasegawa-Johnson, M.A.: Speech Analysis Synthesis and Perception, 3rd edn. (2008)
Mariani, J.: Spoken language processing. Wiley (2009) ISBN 978-1-84821-031-8
Huang, X.D., Ariki, Y., Jack, M.A.: Hidden Markov Models for Speech Recognition. Edinburgh University Press (1990)
Katagiri, S. (ed.): Handbook of Neural Networks for Speech Processing. Artech House (2000) ISBN 0-89006-954-9
Wiggers, P., Rothkrantz, L.J.M., van de Lisdonk, R.: Design and Implementation of a Bayesian Network Speech Recognizer. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds.) TSD 2010. LNCS (LNAI), vol. 6231, pp. 447–454. Springer, Heidelberg (2010)
Šuch, O.: Using min-max Circuits for Speech Recognition. Habilitation thesis, University of Žilina (2013), http://www.savbb.sk/~ondrejs/Phoneme/hab.pdf
Heigold, G., Ney, H., Schlüter, R., Wiesler, S.: Discriminative Training for Automatic Speech Recognition. IEEE Signal Processing Magazine 29(6), 58–69 (2012)
Yager, R.R.: On Ordered Weighted Averaging Aggregation Operators in Multicriteria Decision-making. IEEE Transactions on Systems, Man, and Cybernetics 18(1) (January/February 1988)
Hermansky, H., Ellis, D., Sharma, S.: Tandem connectionist feature extraction for conventional HMM systems. In: Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), Istanbul, Turkey, pp. 1635–1638 (June 2000)
Foltán, S.: Speech recognition by means of fuzzy logical circuits. In: 18th International Conference on Soft Computing, Brno (2012) ISBN 9788021445406
Hastie, T., Tibshirani, R., Friedman, J.: Elements of Statistical Learning. Springer, dataset, http://cran.r-project.org/package=ElemStatLearn
Dean, T., Ruzon, M.A., Segal, M., Shlens, J., Vijayanarasimhan, S., Yagnik, J.: Fast, Accurate Detection of 100,000 Object Classes on a Single Machine. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, Washington (2013)
Klimo, M., Šuch, O.: Memristors can implement fuzzy logic. Cornell University, Ithaka (2011), http://arxiv.org/pdf/1110.2074.pdf
Yager, R.R., Filev, D.P.: Induced Ordered Weighted Averaging Operators. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 29(2) (April 1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Klimo, M., Škvarek, O., Smieško, J., Foltán, S., Šuch, O. (2015). Vowel Recognition Supported by Ordered Weighted Average. In: Sinčák, P., Hartono, P., Virčíková, M., Vaščák, J., Jakša, R. (eds) Emergent Trends in Robotics and Intelligent Systems. Advances in Intelligent Systems and Computing, vol 316. Springer, Cham. https://doi.org/10.1007/978-3-319-10783-7_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-10783-7_27
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10782-0
Online ISBN: 978-3-319-10783-7
eBook Packages: EngineeringEngineering (R0)