Fractional-DCT ADALINE method for Speech Enhancement

Authors(2) :-R. Ram, M. N. Mohanty

Enhancement of speech is an essential task in the most of the field along with social management. The quality of the speechisdegraded mostly in the noisy environment.Also the same can be obtained from the physical disable people. To improve the quality of the speech, different enhancement algorithms can be applied. In this paper an attempt has been taken by the help of adaptive neural network based model. The fractional DCT (FrDCT) has been utilized for the input to the model. Earlier to it the discrete cosine transform (DCT) coefficients are employed to the model for the sake of verifications. That follows the coefficients of FrDCT and the results are compared. The deteriorated speech considers in this are in vehicular environment as well as summer environment with the fan.The results obtained for different noise environment that the FrDCT-ADALINE method outperforms better than the other methods.

Authors and Affiliations

R. Ram
Department of Electronics and Communication Engineering Siksha ]O' Anusandhan University, Bhubaneswar, Odisha, India
M. N. Mohanty
Department of Electronics and Communication Engineering Siksha ]O' Anusandhan University, Bhubaneswar, Odisha, India

Adaptive Linear Neuron, Fractional Discrete Cosine Transform, Filtering, Segmental Signal-to-Noise Ratio, Mean Opinion Score, Speech Enhancement.

  1. Loizou, P., 2007, Speech Enhancement: Theory and Practice. CRC Press.
  2. Haykin, S. S., & Haykin, S. S. , 2009, Neural networks and learning machines. New York: Prentice Hall/Pearson.
  3. Boll,S.F., 1979, Suppression of Acoustic Noise in Speech using Spectral Subtraction.IEEE Transaction ASSP. 113-120.
  4. Upadhyay, N., Karmakar, A., 2015, Speech Enhancement using Spectral Subtraction-type Algorithms: A Comparison and Simulation Study. Elsevier Procedia Computer Science. 55, 574-584.
  5. Ram, R Mohanty, M.N.,2016, Performance Analysis of Adaptive Algorithms for Speech Enhancement Applications. Indian Journal of Science and Technology. 9(44).
  6. Vihari,S., Murthy,A.S., Soni, P., Naik,D.C.,2016, Comparison of Speech Enhancement Algorithms. Procedia Computer Science. 89, 666 – 676.
  7. Fah,L.B., Hussain, A., Samad,S.A., 2000, Speech Enhancement by Noise Cancellation Using Neural Network. IEEE Conf..
  8. Kounovsky, T., Malek,J.,2017, Single Channel Speech Enhancement Using Convolutional Neural Network. IEEE International Workshop of Electronics, Control, Measurement, Signals and their Application to Mechatronics. 1-5.
  9. Daqrouq, K., Abu-Isbeih, I.N., Alfauori, M., 2009, Speech Signal Enhancement Using Neural Network and Wavelet Transform. International Multi-Conference on Systems, Signals and Devices.
  10. Xia,Y., Wang,J., 2015, Low-Dimensional Recurrent Neural Network-based Kalman Filter for Speech Enhancement.Neural Networks 67, 131–139.
  11. Goehring,T., Bolner,F., Monaghan,J.J.M., Dijk, B., Zarowski,A., Bleeck,S., 2017, Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.Hearing Research 344, 183-194.
  12. Ozaktas, H.M., Ankan,O., Kutay,M.A., Bozdaki, G., 1996, Digital Computation of the Fractional Fourier Transform. IEEE Transactions on Signal Processing, 44(9).
  13. Kutay, M.A., Ozaktas, H.M., Arikan, O., Onural, L., 1997, Optimal Filtering in Fractional Fourier Domains. IEEE Transactions on Signal Processing, 45(5).
  14. Zhenli, W., Xiongwei, Z., 2005, On the application of fractional Fourier transform for enhancing noisy speech. IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications Proceedings.
  15. Cariolaro, G., Erseghe, T., Kraniauskas, P., 2002, The Fractional Discrete Cosine Transform. IEEE Transactions on Signal Processing. 50(4).
  16. Ram, R., Mohanty, M.N., 2017, Design of Fractional Fourier Transform based Filter for Speech Enhancement. IJCTA. 10(07), 235-243.
  17. Jeeva, M.P.A., Nagarajan, T., Vijayalakshmi, P., 2016, Discrete Cosine Transform-Derived Spectrum based Speech Enhancement Algorithm using Temporal-Domain Multiband Filtering.IET Journal of Signal Processing.
  18. Ram, R., Mohanty, M.N., 2017, Design of Filter using Fractional-DCTfor Speech Enhancement. Int. Conf on Sustain.able Computing Techniques in Engineering, Science and Management.
  19. Hu, Y., Loizou, P., 2008, Evaluation of objective quality measures for speech enhancement. IEEE Trans. Audio Speech Lang. Process., 16, 229–238.

Publication Details

Published in : Volume 2 | Issue 7 | September 2017
Date of Publication : 2017-09-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 210-218
Manuscript Number : CSEIT174426
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

R. Ram, M. N. Mohanty, "Fractional-DCT ADALINE method for Speech Enhancement", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 7, pp.210-218, September-2017.
Journal URL : http://ijsrcseit.com/CSEIT174426

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