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An Improved Rational Approximation of Bark Scale Using Low Complexity and Low Delay Filter Banks

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Abstract

This paper proposes an algorithm to obtain the sampling factors to model any frequency partitioning so that it is realized using low complexity rational decimated non-uniform filter banks (RDNUFBs). The proposed algorithm is employed to approximate the Bark scale to find a rational frequency partitioning that can be realized using RDNUFBs with less approximation error. The proposed Bark frequency partitioning is found to reduce the average deviation in centre frequency and bandwidth by 65.04% and 48.50%, respectively, and root-mean-square bandwidth deviation by 54.46% when compared to those of the existing perceptual wavelet approximation of Bark scale. In the first filter bank design approach discussed in the paper, a near-perfect reconstruction partially cosine modulated filter bank is employed to obtain the improved Bark frequency partitioning. In the second design approach, the hardware complexity of the PCM-based RDNUFB is reduced by deriving the channels with different sampling factors from the same prototype filter by the method of channel merging. There is a considerable reduction of 40.83% in the number of multipliers when merging of partially cosine modulated channels is employed. It is also found that both the proposed approaches can reduce the delay by 95.17% when compared to the existing rational tree approximation methods and hence, are suitable for real-time applications.

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References

  1. A. Amir, T.S. Bindiya, E. Elias, Low-complexity implementation of efficient reconfigurable structure for cost-effective hearing aids using fractional interpolation. Comput. Electr. Eng. 2019(74), 391–412 (2019)

    Google Scholar 

  2. F. Argenti, B. Brogelli, E. Del Re, Design of pseudo-QMF banks with rational sampling factors using several prototype filters. IEEE Trans. Signal Process. 46(6), 1709–15 (1998)

    Article  Google Scholar 

  3. R. Bregovic, Y.C. Lim, T. Saramaki, Frequency-response masking-based design of nearly perfect-reconstruction two-channel FIR filterbanks with rational sampling factors. IEEE Trans. Circuits Syst. I: Regular Pap. 55(7), 2002–2012 (2008)

    Article  MathSciNet  Google Scholar 

  4. R. Bregovic, T. Saramaki, Design of linear-phase two-channel FIR filter banks with rational sampling factors. In: 2003 International Symposium on Image and Signal Processing and Analysis ISPA, ISPA Proc: 749-754 (2003)

  5. L. T. Cao, R.W Li, Y.Q. Shi, S. Wang, Loudness compensation method based on human auditory for digital hearing aids. In: 2014 7th International Conference on Biomedical Engineering and Informatics, pp. 335–340 (2014)

  6. X.Y. Chen, X.M Xie, G.M Shi, Direct design of near perfect reconstruction linear phase nonuniform filter banks with rational sampling factors. In: 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proc: III253–III256 (2006)

  7. I. Cohen, Enhancement of speech using bark-scaled wavelet packet decomposition. In: 2001 Seventh European Conference on Speech Communication and Technology Proc: 1933–1936 (2001)

  8. A. De Paolis, M. Bikson, J.T. Nelson, J.A. de, M. Packer, L. Cardoso, Analytical and numerical modeling of the hearing system: Advances towards the assessment of hearing damage. Hear. Res. 349, 111–128 (2017)

  9. Y. Deng, V.J. Mathews, B. Farhang-Boroujeny, Low-delay nonuniform pseudo-QMF banks with application to speech enhancement. IEEE Trans. Signal Process. 55(5), 2110–21 (2007)

    Article  MathSciNet  Google Scholar 

  10. O. Farooq, S. Datta, Mel filter-like admissible wavelet packet structure for speech recognition. IEEE Signal Process. Lett. 8(7), 196–8 (2001)

    Article  Google Scholar 

  11. V. Hareesh, T.S. Bindiya, Analysis of different rational decimated filter banks derived from the same set of prototype filters. IEEE Trans. Signal Process. 68, 1923–36 (2020)

    Article  MathSciNet  Google Scholar 

  12. V.Hareesh, T.S Bindiya, Design of low-complex linear-phase non-uniform filter bank to realize wavelet approximation of bark frequency partitioning for real-time applications. Circuits Syst. Signal Process. 1–27(2020)

  13. P.Q Hoang, P.P Vaidyanathan, Non-uniform multirate filter banks: Theory and design. In: 1989 IEEE International Symposium on Circuits and Systems Proc: 371–374 (1989)

  14. Y. Huang, A. Wu, G. Zhang, Y. Li, Extraction of adaptive wavelet packet filter-bank-based acoustic feature for speech emotion recognition. IET Signal Proc. 9(4), 341–8 (2015)

    Article  Google Scholar 

  15. A. Karmakar, A. Kumar, R.K. Patney, Design of optimal wavelet packet trees based on auditory perception criterion. IEEE Signal Process. Lett. 14(4), 240–3 (2007)

    Article  Google Scholar 

  16. J.J. Lee, B.G. Lee, A design of nonuniform cosine modulated filter banks. IEEE Trans. Circuits Syst. II: Analog Digit. Signal Process. 42(11), 732–7 (1995)

    Google Scholar 

  17. Y. Neuvo, Y.D. Cheng-Yu, S. Mitra, Interpolated finite impulse response filters. IEEE Trans. Acoust. Speech Signal Process. 32(3), 563–70 (1984)

    Article  Google Scholar 

  18. A.V. Oppenheim, R.W. Schafer, Digital Signal Processing (Prentice-Hall, Inc., Englewood Cliffs, 1975)

    Google Scholar 

  19. Y. Shao, C.H. Chang, A generalized time-frequency subtraction method for robust speech enhancement based on wavelet filter banks modeling of human auditory system. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 37(4), 877–89 (2007)

    Article  Google Scholar 

  20. S. Tabibi S, A. Kegel, W. K. Lai Dillier, Investigating the use of a Gammatone filterbank for a cochlear implant coding strategy. J. Neurosci. Methods 277, 63–74 (2017)

  21. TIMIT Acoustic-Phonetic Continuous Speech Corpus, National Inst. Standards Technol., Speech Disc 1-1.1, NTIS Order PB91-505 065 (1990)

  22. H. Traunmüller, Analytical expressions for the tonotopic sensory scale. J. Acoust. Soc. Am. 188(1), 97–100 (1990)

    Article  Google Scholar 

  23. P. Upadhyaya P, O. Farooq, M.R Abidi, Mel scaled M-band wavelet filter bank for speech recognition. Int. J. Speech Technol. 21(4), 797–807 (2018)

  24. P.P. Vaidyanathan, Multirate Systems and Filter Banks (Pearson Education, India, 2006)

    Google Scholar 

  25. X.M. Xie, S.C. Chan, T.I. Yuk, Design of linear-phase recombination nonuniform filter banks. IEEE Trans. Signal Process. 54(7), 2809–14 (2006)

    Article  Google Scholar 

  26. X.M. Xie, L. Liang, G Shi G Analysis of realizable rational decimated nonuniform filter banks with direct structure. Prog. Nat. Sci. 18(12), 1501–5 (2008)

  27. W. Zhong, G. Shi, X. Xie, X. Chen, Design of linear-phase nonuniform filter banks with partial cosine modulation. IEEE Trans. Signal Process. 58(6), 3390–5 (2010)

    Article  MathSciNet  Google Scholar 

  28. E. Zwicker, Subdivision of the audible frequency range into critical bands (Frequenzgruppen). J. Acoust. Soc. Am. 33(2), 248–248 (1961)

    Article  Google Scholar 

  29. E. Zwicker, H. Fastl, Psychoacoustics: Facts and Models (Springer Science & Business Media, Cham, 2013)

    Google Scholar 

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Acknowledgements

Authors would like to thank the Department of Science & Technology, Government of India, for supporting this work under the FIST scheme No. SR/FST/ET-I/2017/68.

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Hareesh, V., Bindiya, T.S. An Improved Rational Approximation of Bark Scale Using Low Complexity and Low Delay Filter Banks. Circuits Syst Signal Process (2024). https://doi.org/10.1007/s00034-024-02664-8

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