Open Access
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
Article Number 05007
Number of page(s) 7
Section Modelling and Simulation
Published online 04 March 2020
  1. X. Bao, Mongolian language oriented research on acoustic modeling for speech recognition, Inner Mongolia University, Hohhot, 2016. [Google Scholar]
  2. X. Bao, G. Gao, Acoustic model topology optimization using evolutionary methods, in Conference Proceedings ACPR2011 (Beijing, China), pp.355–361, Nov.2011. [Google Scholar]
  3. X. Bao, G. Gao, J. Zhang, Construction of concise speech recognition systems based on BIC and PSO, Computer Engineering and Applications, 49 (10) 14–17, 2013. [Google Scholar]
  4. X. Bao, G. Gao, J. Zhang, Genetic algorithm based optimization of acoustic model topologies, Computer Engineering and Applications, 50 (14) 5–8, 2014. [Google Scholar]
  5. F. Busetti, Genetic algorithms overview, Mathematical Problems in Engineering, 2015 (21) 1–9, 2001. [Google Scholar]
  6. R. L. Haupt, S. E. Haupt, Practical genetic algorithms, John Wiley & Sons, 2004. [Google Scholar]
  7. D. R. Umarani, V. Selvi, Particle swarm optimization- evolution, overview and applications, International Journal of Engineering Science & Technology, 38 (2) 997–1000, 2010. [Google Scholar]
  8. R. Poli, J. Kennedy, T. Blackwell, Particle swarm optimization, Swarm Intelligence, 1 (1) 33–57, 2007. [CrossRef] [Google Scholar]
  9. Y. del Valle, G. K. Venayagamoorthy, S. Mohagheghi, Particle swarm optimization: basic concepts, variants and applications in power systems, IEEE Transactions on Evolutionary Computation, 12 (2) 171–195, 2008. [CrossRef] [Google Scholar]
  10. D. Sedighizadeh, E. Masehian, Particle swarm optimization methods, taxonomy and applications, International Journal of Computer Theory and Engineering, 1 (5) 486–502, 2009. [CrossRef] [Google Scholar]
  11. J. Schmidhuber, Deep learning in neural networks: an overview, Neural Networks, 61 (10) 85–117, 2015. [Google Scholar]
  12. J. Pan, C. Liu, Z. Wang, Investigation of Deep Neural Networks (DNN) for large vocabulary continuous speech recognition: why DNN Surpasses GMMs in acoustic modeling, in Conference Proceedings 8th International Symposium on Chinese Spoken Language Processing, pp. 301–305, 2012. [Google Scholar]
  13. T. N. Sainath, A. Mohamed, B. Kingsbury, Deep convolutional neural networks for LVCSR, in Conference Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8614–8618, 2013. [Google Scholar]
  14. D. Yu, L. Deng, Automatic speech recognition: a deep learning approach, Springer Publishing Company Incorporated, New York, 2014. [Google Scholar]
  15. L. Deng, D. Yu, Deep learning: methods and applications, Foundations & Trends in Signal Processing, 7 (3) 197–387, 2013. [Google Scholar]

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