Skip to main content
SpringerLink
Log in

Nonlinear Adaptive Speech Enhancement Inspired by Early Auditory Processing

  • Conference paper
Nonlinear Speech Modeling and Applications (NN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3445))

Included in the following conference series:

Abstract

This paper presents non-linear adaptive speech enhancement schemes inspired by features of early auditory processing. A generic multi-microphone sub-band adaptive (MMSBA) framework is described which allows for the manipulation of several factors that may influence the intelligibility and perceived quality of the processed speech. The proposed framework supports inclusion of: non-linear distribution of sub-bands (as in humans), cross-band effects such as lateral inhibition, and robust adaptive metrics for selecting an appropriate coherent or incoherent noise canceller for each sub-band, based on identified features of the band-limited signals from multiple-sensors during silence periods. An efficient higher order statistics (HOS) based speech/non-speech detector is proposed for enabling effective adaptive control of MMSBA filtering against the environment. New hybrid extensions of the MMSBA scheme incorporating neural networks and post-Weiner filtering are also described and their comparative performance assessed in real reverberant environments. Finally, some future research directions for MMSBA based speech enhancement are proposed including possible alternative strategies based on stochastic resonance.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Feng, A.S.: Information processing in the auditory brainstem. Current Opinion in Neurobiology 2, 511–515 (1992)

    Article  Google Scholar 

  2. Plomp, R.: Auditory handicap of hearing impairment & limited benefit of hearing aids. J. Acoust. Soc. Am (JASA) 63, 533–549 (1978)

    Article  Google Scholar 

  3. Gustaffson, H.A., Arlinger, S.D.: Masking of speech by amplitude modulated noise. J. Acoust. Soc. Am. 95, 518–529 (1994)

    Article  Google Scholar 

  4. Darwin, C.J., McKeown, J.D., Kirby, D.: Compensation for transmission channel & speaker effects on vowel quality. Speech Comm. 8, 221–234 (1989)

    Article  Google Scholar 

  5. Campbell, D.R.: Binaural Processing for Hearing Aids. In: Ainsworth, W., Greenberg, S. (eds.) Proceedings of Workshop on Auditory Basis of Speech Perception, Keele University, UK, July 15-19, pp. 253–256 (1996)

    Google Scholar 

  6. Glasberg, B.R., Moore, B.C.J.: Psychoacoustical abilities of subjects with unilateral and bilateral cochlear hearing impairments and their relationship to the ability to understand speech. Scand. Audio. Suppl. 32, 1–25 (1989)

    Google Scholar 

  7. Wightman, F.L., Kistler, D.J.: The dominant role of low-frequency interaural time differences in sound localization. J. Acoust. Soc. Am. 91, 1648–1661 (1992)

    Article  Google Scholar 

  8. Carhart, R., Tillman, T.W., Johnson, K.R.: Effects of interaural time delays on masking by two competing signals. J. Acoust. Soc. Am (JASA) 43, 1223–1230 (1968)

    Article  Google Scholar 

  9. Baer, T., Moore, B.C.J., Gatehouse, S.: Spectral contrast enhancement of speech in noise for listeners with sensorineural hearing impairment: effects on intelligibility, quality and response times. J. Rehab. Res. Dev. 30, 49–72 (1993)

    Google Scholar 

  10. Bernstein, L.R., Trahiotis, C.: Discrimination of interaural envelope correlation and its relation to binaural unmasking at high frequencies. J. Acoust. Soc. Am (JASA) 91, 306–316 (1992)

    Article  Google Scholar 

  11. Culling, J.F., Summerfield, Q.: Perceptual separation of concurrent speech sounds: Absence of cross frequency grouping by common interaural delay. J. Acoust. Soc. Am (JASA) 98, 785–797 (1995)

    Article  Google Scholar 

  12. Durlach, N.: Binaural signal detection: Equalization & cancellation theory. In: Tobias, J.V. (ed.) Foundations of Modern Auditory Theory, vol. II, Academic Press, London (1972)

    Google Scholar 

  13. Ghitza, O.: Auditory models and human performance in tasks related to speech coding and speech recognition. IEEE Trans. Speech & Audio Proc. 2, 115–132 (1994)

    Article  Google Scholar 

  14. Cheng, Y.M., O’Shaughnessy, D.: Speech-enhancement based conceptually on auditory evidence. IEEE Trans. Sig. Proc. 39, 1943–1954 (1991)

    Article  Google Scholar 

  15. Hermansky, H., Tibrewala, S.: Sub-band Based Recognition of Noisy Speech. In: Proc. ICASSP, Munich, April 20-24, pp. 1255–1258 (1997)

    Google Scholar 

  16. Bourlard, H., Dupont, S.: Subband-based speech recognition. In: Proc. ICASSP, Munich, April 20-24, pp. 1255–1258 (1997)

    Google Scholar 

  17. Smith, L.S.: Biologically inspired robust onset detection. J. Acoust. Soc. America 113 (2003)

    Google Scholar 

  18. Toner, E.: Speech Enhancement using Digital Signal Processing. PhD thesis. University of Paisley, UK (1993)

    Google Scholar 

  19. Toner, E., Campbell, D.R.: Speech Enhancement using sub-band intermittent adaption. Speech Communication 12, 253–259 (1993)

    Article  Google Scholar 

  20. Goulding, M.M., Bird, J.S.: Speech enhancement for mobile telephony. IEEE Trans. on Vehicular Technology 39(4), 316–326 (1990)

    Article  Google Scholar 

  21. Hussain, A., Campbell, D.R.: Intelligibility improvements using binaural diverse sub-band processing applied to speech corrupted with automobile noise. IEE Proceedings: Vision, Image & Signal Processing 148, 127–132 (2001)

    Article  Google Scholar 

  22. Wallace, R.B., Goubran, R.A.: Improved tracking adaptive noise canceller for nonstationary environments. IEEE Trans. on Sig. Proc. 40, 700–703 (1992)

    Article  Google Scholar 

  23. Elberling, C., Ludvigsen, C., Keidser, G.: Design &testing of a noise reduction algorithm based on spectral subtraction. Scand. Audiol., Suppl. 38, 39–48 (1993)

    Google Scholar 

  24. Kollmeier, B., Peissig, J., Hohmann, V.: Binaural noise-reduction hearing aid scheme with real-time processing in the frequency domain. Scand. Audiol., Suppl. 38, 28–38 (1993)

    Google Scholar 

  25. Moore, B.C.J., Peters, R.W., Stone, M.A.: Benefits of linear amplification and multichannel compression for speech comprehension in backgrounds with spectral and temporal dips. J. Acoust. Soc. Am. 105, 400–411 (1999)

    Article  Google Scholar 

  26. Soede, W., Bilsen, F.A., Berkhout, A.J.: Assessment of a directional microphone array for hearing impaired listeners. J. Acous. Soc. Am. 94, 799–808 (1993)

    Article  Google Scholar 

  27. Elberling, C., Ludvigsen, C., Keidser, G.: Design &testing of a noise reduction algorithm based on spectral subtraction. Scand. Audiol. Suppl. 38, 39–49 (1993)

    Google Scholar 

  28. Le Bouquin, R., Azirani, A.A., Faucon, G.: Enhancement of speech degraded by coherent and incoherent noise using a cross-spectral estimator. IEEE Trans. Speech & Audio Proc. 5, 484–487 (1997)

    Article  Google Scholar 

  29. Abutalebi, H.R., Sheikhzadeh, H., Brennan, R.L., Freeman, G.H.: A hybrid sub-band system for speech enhancement in diffused noise fields. IEEE Sig. Process. Letters (2003)

    Google Scholar 

  30. Dabis, H.S., Moir, T.J., Campbell, D.R.: Speech enhancement by recursive estimation of differential transfer functions. In: Proceedings of ICSP, Beijing, pp. 345–348 (1990)

    Google Scholar 

  31. Hussain, A.: A Multi-microphone Sub-band Adaptive Speech Enhancement System employing diverse sub-band processing. International Journal of Robotics & Automation 15, 78–84 (2000)

    Google Scholar 

  32. Shields, P., Campbell, D.R.: Improvements in intelligibility of noisy reverberant speech using a binaural sub-band adaptive noise-cancellation processing scheme. J. Acous. Soc. Am. 110, 3232–3242 (2001)

    Article  Google Scholar 

  33. Hussain, A.: Multi-sensor Neural Network processing of Noisy Speech. International Journal of Neural Systems 9, 467–472 (1999)

    Article  Google Scholar 

  34. Hussain, A.: Non-linear Speech Processing using Neural Networks based Adaptive Filtering. In: Proc. 4th IEEE INMIC, Islamabad, September 10-11 (2000)

    Google Scholar 

  35. Soraghan, J., Hussain, A., Alkulaibi, A., Durrani, T.S.: Higher Order Statistics based nonlinear speech analysis. Journal of Control and Intelligent Systems 30, 11–18 (2002)

    Google Scholar 

  36. Greenwood, D.D.: A cochlear frequency-position function for several species-29 years later. J. Acoustic Soc. Amer. 86, 2592–2605 (1990)

    Article  Google Scholar 

  37. Vaseghi, S.V.: Advanced signal processing and digital noise reduction. John Wiley & Sons, Chichester (2000)

    Book  Google Scholar 

  38. Ferrara, E.R., Widrow, B.: Multi-channel Adaptive Filtering for signal enhancement. IEEE Trans. on Acoustics, Speech and Signal Proc. 29, 766–770 (1981)

    Article  MATH  Google Scholar 

  39. Le Bouquin, R., Faucon, G.: Study of a voice activity detector and its influence on a noise reduction system. Speech Communication 16, 245–254 (1995)

    Article  Google Scholar 

  40. Yoma, N.B., McInnes, F., Jack, M.: Lateral inhibition Net and Weighted Matching Algorithms for speech recognition in noise. Proc. IEE Vision, Image & Signal Processing 143, 324–330 (1996)

    Article  Google Scholar 

  41. Bahoura, M., Rouat, J.: A new approach for wavelet speech enhancement. In: Proc. EUROSPEECH, pp. 1937–(2001)

    Google Scholar 

  42. Bahoura, M., Rouat, J.: Wavelet speech enhancement based on the Teager Energy Operator. IEEE Signal Proc. Lett. 8, 10–12 (2001)

    Article  Google Scholar 

  43. Nikias, C., Raghuvers, M.: Bispectrum estimation: A digital signal procession framework. Proc. IEEE. 75, 869–891 (1987)

    Article  Google Scholar 

  44. Lynch, M.R., Holden, S.B., Rayner, P.J.W.: Complexity Reduction in Volterra Connectionist Networks using a Self-Structuring LMS Algorithm. In: Proc. IEE Second Intern. Conf. Artificial Neural Networks, pp. 44–48 (1991)

    Google Scholar 

  45. Gammaitoni, L., Hanggi, Jung, P., Marchesoni, P.: Stochastic resonance. Review Modern Physics 70, 223–287 (1998)

    Article  Google Scholar 

  46. Petracchi, D., Gebeshuber, I.C., DeFelice, L.J., Holden, A.V.: Stochastic resonance in biologocal systems. Chaos, Solutions and Fractals 11, 1819–1822 (2000)

    Article  MATH  Google Scholar 

  47. Douglas, J.K., Wilkens, L., Pantazelou, E., Moss, F.: Noise enhancement of information transfer in crayfish mechanoreceptor by stochastic resonance. Nature 365, 337–340 (1993)

    Article  Google Scholar 

  48. Fauve, F.: Stochastic resonance in a bistable system. Phys. Lett. 97A, 5–7 (1983)

    Google Scholar 

  49. Weisenfeld, M.F.: Stochastic resonance and the benefits of noise: from ice ages to the crayfish and SQUIDs. Nature 373, 33–36 (1995)

    Article  Google Scholar 

  50. Douglas, K., Wilkens, L., Pantazelou, E., Moss, F.: Noise enhancement of information transfer in crayfish mechanoreceptor by stochastic resonance. Nature 365, 337–340 (1995)

    Article  Google Scholar 

  51. Anderson, J.S., Lampl, I., Gillespie, D.C., Ferster, D.: The contribution of noise to contrast invariance of orientation tuning in Cat visual cortex. Science 290, 1968–1972 (2000)

    Article  Google Scholar 

  52. Levin, J.E., Miller, J.P.: Broadband neural encoding in the cricket cercal sensory system enhanced by stochastic resonance. Nature 380, 165–168 (1996)

    Article  Google Scholar 

  53. Usher, M., Feingold, M.: Stochastic resonance in the speed of memory retrieval. Biological Cybernetics 83, L11-L16 (2000)

    Article  Google Scholar 

  54. Mori, T., Kai, S.: Noise-induced entrainment and stochastic resonance in human brain waves. Phys. Rev. Lett. 88, 1–4 (2002)

    Article  Google Scholar 

  55. Hohn, N., Burkitt, A.N.: Modelling the neural response to speech: stochastic resonance and coding of vowel-like stimuli. In: IEEE EMBS Conference, Monash University (2001)

    Google Scholar 

  56. Luchinsky, D.G., Mannella, R., McClintock, P.V.E., Stocks, N.G.: Stochastic resonance in electrical circuits II. Nonconventional stochastic resonance. IEEE Trans. Circuits and Systems 46, 1215–1224 (1999)

    Google Scholar 

  57. Stocks, N.G.: Information transmission in parallel arrays of threshold elements: suprathreshold stochastic resonance. Phy. Rev. E. 63, 1–9 (2001)

    Article  Google Scholar 

  58. Stocks, N.G., Allingham, G., Morse, R.P.: The application of suprathreshold stochastic resonance to cochlear implant coding. J. Fluctuation and noise letters 2, 169–181 (2002)

    Article  Google Scholar 

  59. Gammaitoni, L.: Stochastic resonance and the dithering effect in threshold physical systems. Physical Review E 52, 4691–4698 (1995)

    Article  Google Scholar 

  60. Longtin, A., Bulsara, A., Moss, F.: Time-interval sequences in bistable systems and noiseinduced transmission of information by sensory neurons. Phys. Rev Lett. 67, 656–659 (1991)

    Article  Google Scholar 

  61. Collins, J.J., Chow, C.C., Capela, A.C., Imhoff, T.T.: Aperiodic stochastic resonance. Phys. Rev. E. 54, 5575–5584 (1996)

    Article  Google Scholar 

  62. Stemmler, M.: A Single Spike Suffices: the simplest form of stochastic resonance in model neurons. Network: Computation in Neural Systems 7, 687–716 (1996)

    Article  MATH  Google Scholar 

  63. Benzi, R., Sutera, A., Vulpiiani, A.: The mechanism of stochastic resonance. J. Phys. A 14, 453–457 (1981)

    Article  MathSciNet  Google Scholar 

  64. Nicolis, C., Nicolis, G.: Stochastic aspects of climatic transitions - response to periodic forcing. Tellus 34, 1–9 (1982)

    Article  MathSciNet  Google Scholar 

  65. Benzi, R., Parisi, G., Sutera, A., Vulpiani, A.: Stochastic resonance in climatic changes. Tellus 34, 10–16 (1982)

    Article  Google Scholar 

  66. McNamara, B., Wiesenfeld, K., Roy, R.: Observation of stochastic resonance in a ring laser. Phys. Rev. Lett. 60, 2626–2629 (2002)

    Article  Google Scholar 

  67. Gluckman, B.J., Netoff, T.I., Neel, E.J., Dittoand, W.L., Spano, M.L., Schiff, S.J.: Stochastic resonance in a neuronal network from a mammalian brain. Physical Review Letters 77, 4098–4101 (1996)

    Article  Google Scholar 

  68. Morse, R.P., Evans, E.F.: Enhancement of vowel coding for cochlear implants by addition of noise. Nature Medicine 2, 928–932 (1996)

    Article  Google Scholar 

  69. Mtetwa, N., Smith, L.S.: Precision constrained stochastic resonance in a feed forward neural network. IEEE Transactions on Neural Networks (2004) (in press)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Cognitive and Computational Neuroscience, University of Stirling, Stirling, FK9 4LA, Scotland, UK

    Amir Hussain & Nhamo Mtetwa

  2. Institute of Communications & Signal Processing, University of Strathclyde, Glasgow, G1 1XW, Scotland, UK

    Tariq S. Durrani

  3.  , P.O. Box 4822, Jeddah, 21412, Saudi Arabia

    Ali Alkulaibi

Authors
  1. Amir Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tariq S. Durrani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ali Alkulaibi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nhamo Mtetwa
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. CNRS LTCI/TSI Paris, 46 rue Barrault, 75634, Paris Cedex 13, France

    Gérard Chollet

  2. Department of Psychology, Second University of Naples, and IIASS, Via Pellegrino 19, 84019, Vietri sul Mare, SA, Italy

    Anna Esposito

  3. Escola Universitària Politècnica de Mataró, Universitat Politècnica de Catalunya, Barcelona, Spain

    Marcos Faundez-Zanuy

  4. Dipartimento di Fisica “E.R. Caianiello”, Università degli Studi di Salerno, Via S. Allende, 84081, Baronissi, SA, Italy

    Maria Marinaro

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hussain, A., Durrani, T.S., Alkulaibi, A., Mtetwa, N. (2005). Nonlinear Adaptive Speech Enhancement Inspired by Early Auditory Processing. In: Chollet, G., Esposito, A., Faundez-Zanuy, M., Marinaro, M. (eds) Nonlinear Speech Modeling and Applications. NN 2004. Lecture Notes in Computer Science(), vol 3445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11520153_13

Download citation

  • DOI: https://doi.org/10.1007/11520153_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27441-4

  • Online ISBN: 978-3-540-31886-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation