Skip to main content
Top

2018 | OriginalPaper | Chapter

Analysis of Least Mean Square and Recursive Least Squared Adaptive Filter Algorithm for Speech Enhancement Application

Authors : Mrinal Bachute, R. D. Kharadkar

Published in: Smart and Innovative Trends in Next Generation Computing Technologies

Publisher: Springer Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Speech enhancement is a vital area of research, the performance of speech based human machine applications such as automatic speech recognition system, in car communication depends on the quality of speech communicated. Different methodologies have been used by various researchers to improve the quality of speech signal. In this paper an attempt is made to analyze the performance of Least Mean Square (LMS) and Recursive Least Squared (RLS) adaptive filter algorithm for speech enhancement application. The performance indices used for the evaluations is Mean Square Error (MSE), Signal to Noise Ration (SNR) and execution time. The detail analysis is done and experimentally the results are validated and certain modifications are suggested in the algorithm. The experimentation revels that LMS have fast convergence than RLS. The computational complexity of RLS is very high as compared to LMS.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Jie, Y., Zhenli, W.: On the application of variable-step adaptive noise cancelling for improving the robustness of speech recognition. In: ISECS International Colloquium on Computing, Communication, Control, and Management 2009 CCCM 2009, vol. 2, pp. 419–422. IEEE (2009) Jie, Y., Zhenli, W.: On the application of variable-step adaptive noise cancelling for improving the robustness of speech recognition. In: ISECS International Colloquium on Computing, Communication, Control, and Management 2009 CCCM 2009, vol. 2, pp. 419–422. IEEE (2009)
2.
go back to reference Pandey, A., Malviya, L.D., Sharma, V.: Comparative study of LMS and NLMS algorithms in adaptive equalizer. Int. J. Eng. Res. Appl. (IJERA) 2(3), 1584–1587 (2012) Pandey, A., Malviya, L.D., Sharma, V.: Comparative study of LMS and NLMS algorithms in adaptive equalizer. Int. J. Eng. Res. Appl. (IJERA) 2(3), 1584–1587 (2012)
3.
go back to reference Douglas, S.C., Pan, W.: Exact expectation analysis of the LMS adaptive filter. IEEE Trans. Signal Process. 43(12), 2863–2871 (1995)CrossRef Douglas, S.C., Pan, W.: Exact expectation analysis of the LMS adaptive filter. IEEE Trans. Signal Process. 43(12), 2863–2871 (1995)CrossRef
4.
go back to reference Chu, H.S., An, C.K.: Design of the adaptive noise canceler using neural network with backpropagation algorithm. In: Proceedings the Third Russian-Korean International Symposium on Science and Technology, 1999, KORUS 1999, vol. 2, pp. 762–764. IEEE (1999) Chu, H.S., An, C.K.: Design of the adaptive noise canceler using neural network with backpropagation algorithm. In: Proceedings the Third Russian-Korean International Symposium on Science and Technology, 1999, KORUS 1999, vol. 2, pp. 762–764. IEEE (1999)
5.
go back to reference Hu, Y., Loizou, P.C.: Subjective comparison and evaluation of speech enhancement algorithms. Speech Commun. J. SPCOM Sci. Direct 49, 588–601 (2006)CrossRef Hu, Y., Loizou, P.C.: Subjective comparison and evaluation of speech enhancement algorithms. Speech Commun. J. SPCOM Sci. Direct 49, 588–601 (2006)CrossRef
6.
go back to reference Caraiscos, C., Liu, B.: A round of error analysis of LMS adaptive algorithm. IEEE Trans. Acoust. Speech Signal Process. 32, 34–41 (2000)CrossRef Caraiscos, C., Liu, B.: A round of error analysis of LMS adaptive algorithm. IEEE Trans. Acoust. Speech Signal Process. 32, 34–41 (2000)CrossRef
7.
go back to reference Gardner, W.: Learning characteristics of scholastic gradient descent algorithms: a general study analysis & critique. IEEE Sig. Process. 6, 113–133 (2010)CrossRef Gardner, W.: Learning characteristics of scholastic gradient descent algorithms: a general study analysis & critique. IEEE Sig. Process. 6, 113–133 (2010)CrossRef
9.
go back to reference Douglas, S.C., Pan, W.: Exact expectation analysis of the LMS adaptive filter’. IEEE Trans. Sig. Process. 43(12), 2863–2871 (1995)CrossRef Douglas, S.C., Pan, W.: Exact expectation analysis of the LMS adaptive filter’. IEEE Trans. Sig. Process. 43(12), 2863–2871 (1995)CrossRef
11.
go back to reference Douglas, S.C.: Exact expectation analysis without the independence assumption of the LMS adaptive filter. IEEE Trans. Sig. Process. 43(12), 2863–2871 (2000)CrossRef Douglas, S.C.: Exact expectation analysis without the independence assumption of the LMS adaptive filter. IEEE Trans. Sig. Process. 43(12), 2863–2871 (2000)CrossRef
12.
go back to reference Yang, F., Wu, M., Ji, P., Yang, J.: An improved multiband-structured subband adaptive filter algorithm. 19(10) 647–650 (2012) Yang, F., Wu, M., Ji, P., Yang, J.: An improved multiband-structured subband adaptive filter algorithm. 19(10) 647–650 (2012)
13.
go back to reference Sami, S., Padmaja, P.: Speech enhancement using fast adaptive Kalman filtering algorithm along with weighting filter. 2(5) 387–390 (2013) Sami, S., Padmaja, P.: Speech enhancement using fast adaptive Kalman filtering algorithm along with weighting filter. 2(5) 387–390 (2013)
14.
go back to reference Ravi, B., Kumar, T.K.: Speech enhancement using kernel and normalized kernel affine projection. 4(4), 129–138 (2013) Ravi, B., Kumar, T.K.: Speech enhancement using kernel and normalized kernel affine projection. 4(4), 129–138 (2013)
15.
go back to reference Widrow, B., Stearns, S.D.: Adaptive Signal Processing, 4th edn. Cliff, Prentice Hall, Upper Saddle River (2009)MATH Widrow, B., Stearns, S.D.: Adaptive Signal Processing, 4th edn. Cliff, Prentice Hall, Upper Saddle River (2009)MATH
16.
go back to reference Haykin, S.: Adaptive Filter Theory. Pearson Education, London (2011)MATH Haykin, S.: Adaptive Filter Theory. Pearson Education, London (2011)MATH
17.
go back to reference Farhang Boroujeny, B.: Adaptive Filters: Theory and Applications. Wiley Publications, Hoboken (2006)MATH Farhang Boroujeny, B.: Adaptive Filters: Theory and Applications. Wiley Publications, Hoboken (2006)MATH
18.
go back to reference Hayes, M.H.: Statistical Digital Signal Processing and Modeling. Wiley, Hoboken, pp. 493–552 (1996) Hayes, M.H.: Statistical Digital Signal Processing and Modeling. Wiley, Hoboken, pp. 493–552 (1996)
19.
go back to reference Haykin, S.: Adaptive Filter Theory. Prentice-Hall Inc, Upper Saddle River (1996)MATH Haykin, S.: Adaptive Filter Theory. Prentice-Hall Inc, Upper Saddle River (1996)MATH
20.
go back to reference Bachute, M.: Performance Evaluation of PSO based Speech Enhancement Technique for Speech Communication System Technical Journal of Institution of Engineers (India) Pune Local Center, India, October 2013. ISBN 978-81-924990-1-7 Bachute, M.: Performance Evaluation of PSO based Speech Enhancement Technique for Speech Communication System Technical Journal of Institution of Engineers (India) Pune Local Center, India, October 2013. ISBN 978-81-924990-1-7
21.
go back to reference Bachute, M.R., Kharadkar, R.D.: Performance analysis and comparison of complex LMS, sign LMS and RLS algorithms for speech enhancement application. IJCSN Int. J. Comput. Sci. Netw. 4(5) (2002) Bachute, M.R., Kharadkar, R.D.: Performance analysis and comparison of complex LMS, sign LMS and RLS algorithms for speech enhancement application. IJCSN Int. J. Comput. Sci. Netw. 4(5) (2002)
22.
go back to reference Bachute, M.R., Kharadkar, R.D.: Performance analysis and comparison of complex LMS, sign LMS and RLS algorithms for speech enhancement application Bachute, M.R., Kharadkar, R.D.: Performance analysis and comparison of complex LMS, sign LMS and RLS algorithms for speech enhancement application
23.
go back to reference Bachute, M., Kharadkar, R.D.: Analysis and implementation of time-varying least mean square algorithm and modified Time-Varying LMS for speech enhancement. Int. J. Sci. Res. (IJSR). ISSN (Online) 2319-7064, Index Copernicus Value (2013): 6.14, Impact Factor (2013) Bachute, M., Kharadkar, R.D.: Analysis and implementation of time-varying least mean square algorithm and modified Time-Varying LMS for speech enhancement. Int. J. Sci. Res. (IJSR). ISSN (Online) 2319-7064, Index Copernicus Value (2013): 6.14, Impact Factor (2013)
Metadata
Title
Analysis of Least Mean Square and Recursive Least Squared Adaptive Filter Algorithm for Speech Enhancement Application
Authors
Mrinal Bachute
R. D. Kharadkar
Copyright Year
2018
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-8657-1_45

Premium Partner