Abstract
This paper deals with automatic optimization of free decoding parameters. We propose using a Simplified Simultaneous Perturbation Stochastic Approximation algorithm to optimize these parameters. This method provides a significant reduction in computational and labor costs. We also demonstrate that the proposed method successfully copes with the optimization of parameters for a specific target real-time factor, for all the databases we tested.
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.
Similar content being viewed by others
References
Stein, D., Schwenninger, J., Stadtschnitzer, M.: Simultaneous perturbation stochastic approximation for automatic speech recognition. In: Proc. of the INTERSPEECH, Lyon, France, August 25-29, pp. 622–626 (2013)
El Hannani, A., Hain, T.: Automatic optimization of speech decoder parameters. Signal Processing Letters 17(1), 95–98 (2010), doi:10.1109/LSP.2009.2033967
Mak, B., Ko, T.: Automatic estimation of decoding parameters using large-margin iterative linear programming. In: Proc. of the INTERSPEECH, Brighton, United Kingdom, September 6-10, pp. 1219–1222 (2009)
Kacur, J., Korosi, J.: An accuracy optimization of a dialog ASR system utilizing evolutional strategies. In: Proc. of the ISPA, Istanbul, Turkey, September 27-29, pp. 180–184 (2007)
Spall, J.C.: Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control 37(3), 332–341 (1992), doi:10.1109/9.119632
Spall, J.C.: Implementation of the simultaneous perturbation algorithm for stochastic optimization. IEEE Transactions on Aerospace and Electronic Systems 34(3), 817–823 (1998), doi:10.1109/7.705889
Kiefer, J., Wolfowitz, J.: Stochastic Estimation of the Maximum of a Regression Function. Ann. Math. Stat. 23(3), 462–466 (1952)
Yue, X.: Improved Simultaneous Perturbation Stochastic Approximation and Its Application in Reinforcement Learning. In: Proc. of the International Conference on Computer Science and Software Engineering, Wuhan, Hubei, December 12-14, vol. 1, pp. 329–332 (2008)
Korenevsky, M., Bulusheva, A., Levin, K.: Unknown Words Modeling in Training and Using Language Models for Russian LVCSR System. In: Proc. of the SPECOM, Kazan, Russia, September 27-30, pp. 144–150 (2011)
Yurkov, P., Korenevsky, M., Levin, K.: An Improvement of robustness to speech loudness change for an ASR system based on LC-RC features. In: Proc. of the SPECOM, Kazan, Russia, September 27-30, pp. 62–66 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Romanenko, A., Zatvornitsky, A., Medennikov, I. (2014). Simplified Simultaneous Perturbation Stochastic Approximation for the Optimization of Free Decoding Parameters. In: Ronzhin, A., Potapova, R., Delic, V. (eds) Speech and Computer. SPECOM 2014. Lecture Notes in Computer Science(), vol 8773. Springer, Cham. https://doi.org/10.1007/978-3-319-11581-8_50
Download citation
DOI: https://doi.org/10.1007/978-3-319-11581-8_50
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11580-1
Online ISBN: 978-3-319-11581-8
eBook Packages: Computer ScienceComputer Science (R0)