Skip to main content
SpringerLink
Log in

Introduction

  • Chapter
Speech Dereverberation

Part of the book series: Signals and Commmunication Technology ((SCT))

Abstract

Acoustic reverberation will be introduced in this chapter in the context of telecommunication. The adverse effects on speech caused by reverberation are problematic, in particular, in hands-free terminals operating typically at arms-length from the talker’s lips. This introductory chapter will provide a system description of room reverberation and will formulate mathematically the dereverberation problem in its most direct form so as to introduce and underpin the more detailed presentation in subsequent chapters. Elements of room acoustics will also be introduced where needed, though detailed study of acoustics is not the aim of this text.

At the time of writing this, dereverberation is a topic of study with many important research questions remaining as yet unanswered. Whilst reviewing the relevant literature later in this chapter, it is intended both to describe the state-of-the-art and to highlight some of the significant open issues. Whereas the former aims to consolidate, perhaps for the first time, the known achievements to date of the research community, the latter aims to highlight potential avenues of future research.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. Affes, S., Grenier, Y.: A signal subspace tracking algorithm for microphone array processing of speech. IEEE Trans. Speech Audio Process. 5(5), 425–437 (1997)

    Article  Google Scholar 

  2. Allen, J.B.: Synthesis of pure speech from a reverberant signal. U.S. Patent No. 3786188 (1974)

    Google Scholar 

  3. Allen, J.B., Berkley, D.A.: Image method for efficiently simulating small-room acoustics. J. Acoust. Soc. Am. 65(4), 943–950 (1979)

    Article  Google Scholar 

  4. Allen, J.B., Berkley, D.A., Blauert, J.: Multimicrophone signal-processing technique to remove room reverberation from speech signals. J. Acoust. Soc. Am. 62(4), 912–915 (1977)

    Article  Google Scholar 

  5. BBC, U.: Iceland comes first in broadband. [Online] (2006). URL http://news.bbc. co.uk/1/hi/technology/4903776.stm

    Google Scholar 

  6. Benesty, J., Makino, S., Chen, J. (eds.): Speech enhancement. Springer (2005)

    Google Scholar 

  7. Benesty, J., Sondhi, M.M., Huang, Y. (eds.): Springer handbook of speech processing. Springer (2007)

    Google Scholar 

  8. Bolt, R.H., MacDonald, A.D.: Theory of speech masking by reverberation. J. Acoust. Soc. Am. 21(6), 577–580 (1949)

    Article  Google Scholar 

  9. Bradley, J.S., Sato, H., Picard, M.: On the importance of early reflections for speech in rooms. J. Acoust. Soc. Am. 113(6), 3233–3244 (2003)

    Article  Google Scholar 

  10. Brandstein, M.S., Griebel, S.M.: Nonlinear, model-based microphone array speech enhancement. In: S.L. Gay, J. Benesty (eds.) Acoustic Signal Processing For Telecommunication, pp. 261–279. Kluwer Academic Publishers (2000)

    Google Scholar 

  11. Brandstein, M.S., Ward, D.B. (eds.): Microphone arrays: Signal processing techniques and applications, 1 edn. Springer (2001)

    Google Scholar 

  12. Cherry, C.: On human communications, third edn. MIT Press (1980)

    Google Scholar 

  13. Davis, G.M. (ed.): Noise reduction in speech applications. CRC Press (2002)

    Google Scholar 

  14. Delcroix, M., Hikichi, T., Miyoshi, M.: Precise dereverberation using multichannel linear prediction. IEEE Trans. Audio, Speech, Lang. Process. 15(2), 430–440 (2007)

    Article  Google Scholar 

  15. Elko, G.W.: Microphone array systems for hands-free telecommunication. Speech Communication 20(3-4), 229–240 (1996)

    Article  Google Scholar 

  16. Evers, C., Hopgood, J.R.: Parametric modelling for single-channel blind dereverberation of speech from a moving speaker. IET Communications 2, 59–74 (2008)

    MathSciNet  Google Scholar 

  17. Evers, C., Hopgood, J.R., Bell, J.: Acoustic models for blind source dereverberation using sequential Monte Carlo methods. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP) (2008)

    Google Scholar 

  18. Evers, C., Hopgood, J.R., Bell, J.: Blind speech dereverberation using batch and sequential Monte Carlo methods. In: Proc. Int. Symp. on Circuits and Systems (2008)

    Google Scholar 

  19. Flanagan, J.L., Johnston, J.D., Zahn, R., Elko, G.W.: Computer-steered microphone arrays for sound transduction in large rooms. J. Acoust. Soc. Am. 78(5), 1508–1518 (1985)

    Article  Google Scholar 

  20. Flanagan, J.L., Surendran, A.C., Jan, E.E.: Spatially selective sound capture for speech and audio processing. Speech Communication 13(1-2), 207–222 (1993)

    Article  Google Scholar 

  21. Furuya, K., Kaneda, Y.: Two-channel blind deconvolution for non-minimum phase impulse responses. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 1315–1318 (1997)

    Google Scholar 

  22. Gannot, S., Burshtein, D., Weinstein, E.: Signal enhancement using beamforming and nonstationarity with applications to speech. IEEE Trans. Signal Process. 49(8), 1614–1626 (2001)

    Article  Google Scholar 

  23. Gannot, S., Moonen, M.: Subspace methods for multi-microphone speech dereverberation. EURASIP J. on App. Signal Process. 2003(11), 1074–1090 (2003)

    Article  MATH  Google Scholar 

  24. Gaubitch, N.D.: Blind identification of acoustic systems and enhancement of reverberant speech. Ph.D. thesis, Imperial College London (2007)

    Google Scholar 

  25. Gaubitch, N.D., Hasan, M.K., Naylor, P.A.: Generalized optimal step-size for blind multichannel LMS system identification. IEEE Signal Process. Lett. 13(10), 624–627 (2006)

    Article  Google Scholar 

  26. Gaubitch, N.D., Hasan, M.K., Naylor, P.A.: Noise robust adaptive blind identification using spectral constraints. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. V–93–V–96. Toulouse, France (2006)

    Google Scholar 

  27. Gaubitch, N.D., Naylor, P.A.: Spatiotemporal averaging method for enhancement of reverberant speech. In: Proc. IEEE Int. Conf. Digital Signal Processing (DSP). Cardiff, UK (2007). DOI 10.1109/ICDSP.2007.4288655

    Google Scholar 

  28. Gaubitch, N.D., Naylor, P.A., Ward, D.B.: Multi-microphone speech dereverberation using spatio-temporal averaging. In: Proc. European Signal Processing Conf. (EUSIPCO), pp. 809–812. Vienna, Austria (2004)

    Google Scholar 

  29. Gaubitch, N.D., Ward, D.B., Naylor, P.A.: Statistical analysis of the autoregressive modeling of reverberant speech. J. Acoust. Soc. Am. 120(6), 4031–4039 (2006)

    Article  Google Scholar 

  30. Gay, S.L., Benesty, J. (eds.): Acoustic signal processing for telecommunication. Kluwer Academic Publishers (2000)

    Google Scholar 

  31. Gillespie, B.W., Malvar, H.S., Florêncio, D.A.F.: Speech dereverberation via maximumkurtosis subband adaptive filtering. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 6, pp. 3701–3704 (2001)

    Google Scholar 

  32. Grenier, Y., Affes, S.: Microphone array response to speaker movements. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 1, pp. 247–250 (1997)

    Google Scholar 

  33. Griebel, S.M.: A microphone array system for speech source localization, denoising and dereverberation. Ph.D. thesis, Harvard University, Cambridge, Massachusetts (2002)

    Google Scholar 

  34. Griebel, S.M., Brandstein, M.S.: Wavelet transform extrema clustering for multi-channel speech dereverberation. In: Proc. Int. Workshop Acoust. Echo Noise Control (IWAENC). Pocono Manor, Pennsylvania (1999)

    Google Scholar 

  35. Griebel, S.M., Brandstein, M.S.: Microphone array speech dereverberation using coarse channel estimation. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 1, pp. 201–204 (2001)

    Google Scholar 

  36. Gürelli, L., Nikias, C.L.: EVAM: An eigenvector-based algorithm for multichannel blind deconvolution of input colored signals. IEEE Trans. Signal Process. 43(1), 143–149 (1995)

    Article  Google Scholar 

  37. Haas, H.: The influence of a single echo on the audibility of speech. J. Audio Eng. Soc. 20, 145–159 (1972)

    Google Scholar 

  38. Habets, E.A.P.: Multi-channel speech dereverberation based on a statistical model of late reverberation. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 4, pp. iv/173–iv/176. Philadelphia (2005)

    Google Scholar 

  39. Habets, E.A.P.: Single- and multi-microphone speech dereverberation using spectral enhancement. Ph.D. thesis, Technische Universiteit Eindhoven (2007). URL http:// alexandria.tue.nl/extra2/200710970.pdf

    Google Scholar 

  40. Haneda, Y., Makino, S., Kaneda, Y.: Common acoustical pole and zero modeling of room transfer functions. IEEE Trans. Speech Audio Process. 2(2), 320–328 (1994)

    Article  Google Scholar 

  41. Hänsler, E., Schmidt, G. (eds.): Topics in acoustic echo and noise control. Springer (2006)

    Google Scholar 

  42. Hasan, M.K., Benesty, J., Naylor, P.A., Ward, D.B.: Improving robustness of blind adaptive multichannel identification algorithms using constraints. In: Proc. European Signal Processing Conf. (EUSIPCO). Antalya, Turkey (2005)

    Google Scholar 

  43. Haykin, S.: Adaptive filter theory, 4 edn. Prentice Hall, Upper Saddle River, N.J. (2001)

    Google Scholar 

  44. Hikichi, T., Delcroix, M., Miyoshi, M.: Inverse filtering for speech dereverberation less sensitive to noise. In: Proc. Int. Workshop Acoust. Echo Noise Control (IWAENC), pp. 1–4 (2006)

    Google Scholar 

  45. Hikichi, T., Delcroix, M., Miyoshi, M.: On robust inverse filter design for room transfer function fluctuations. In: Proc. European Signal Processing Conf. (EUSIPCO) (2006)

    Google Scholar 

  46. Hikichi, T., Delcroix, M., Miyoshi, M.: Inverse filtering for speech dereverberation less sensitive to noise and room transfer function fluctuations. EURASIP J. Advances in Signal Processing 2007, 1–12 (2007)

    Article  Google Scholar 

  47. Hopgood, J.R., Rayner, P.J.W.: A probabilistic framework for subband autoregressive models applied to room acoustics. In: Proc. IEEE Workshop Statistical Signal Processing, pp. 492–495 (2001)

    Google Scholar 

  48. Hopgood, J.R., Rayner, P.J.W.: Blind single channel deconvolution using nonstationary signal processing. IEEE Trans. Speech Audio Process. 11(5), 476–488 (2003)

    Article  Google Scholar 

  49. Huang, Y., Benesty, J.: Adaptive multi-channel least mean square and Newton algorithms for blind channel identification. Signal Processing 82(8), 1127–1138 (2002)

    Article  MATH  Google Scholar 

  50. Huang, Y., Benesty, J.: A class of frequency-domain adaptive approaches to blind multichannel identification. IEEE Trans. Signal Process. 51(1), 11–24 (2003)

    Article  MathSciNet  Google Scholar 

  51. Huang, Y., Benesty, J., Chen, J.: A blind channel identification-based two-stage approach to separation and dereverberation of speech signals in a reverberant environment. IEEE Trans. Speech Audio Process. 13(5), 882–895 (2005)

    Article  Google Scholar 

  52. Huang, Y., Benesty, J., Chen, J.: Optimal step size of the adaptive multichannel LMS algorithm for blind SIMO identification. IEEE Signal Process. Lett. 12(3), 173–176 (2005)

    Article  Google Scholar 

  53. Jan, E., Flanagan, J.L.: Microphone arrays for speech processing. In: Int. Symposium on Signals, Systems, and Electronics, pp. 373–376 (1995)

    Google Scholar 

  54. Jan, E., Svazier, P., Flanagan, J.L.: Matched-filter processing of microphone array for spatial volume selectivity. In: Proc. Int. Symp. on Circuits and Systems, vol. 2, pp. 1460–1463 (1995)

    Google Scholar 

  55. Kennedy, R.A., Radlovi´c, B.D.: Iterative cepstrum-based approach for speech dereverberation. In: Proc. Int. Symposium on Signal Processing and Its Applications (ISSPA), vol. 1, pp. 55–58 (1999)

    Google Scholar 

  56. Kuttruff, H.: Room acoustics, 4 edn. Taylor & Francis (2000)

    Google Scholar 

  57. Lebart, K., Boucher, J.M., Denbigh, P.N.: A new method based on spectral subtraction for speech dereverberation. Acta Acoustica 87, 359–366 (2001)

    Google Scholar 

  58. Li, Z., Duraiswami, R.: Flexible and optimal design of spherical microphone arrays for beamforming. IEEE Trans. Audio, Speech, Lang. Process. 15(2), 702–714 (2007)

    Article  Google Scholar 

  59. Lin, X., Gaubitch, N.D., Naylor, P.A.: Two-stage blind identification of SIMO systems with common zeros. In: Proc. European Signal Processing Conf. (EUSIPCO). Florence, Italy (2006)

    Google Scholar 

  60. Loizou, P.C.: Speech enhancement theory and practice. Taylor & Francis (2007)

    Google Scholar 

  61. Meyer, J., Agnello, T.: Spherical microphone array for spatial sound recording. In: Audio Engineering Society, 115th Convention, preprint 5975. New York (2003)

    Google Scholar 

  62. Miyoshi, M., Kaneda, Y.: Inverse filtering of room acoustics. IEEE Trans. Acoust., Speech, Signal Process. 36(2), 145–152 (1988)

    Article  Google Scholar 

  63. Mobile Operators Association: History of cellular mobile communications. [Online] (2005). URL http://www.mobilemastinfo.com/information/history.htm

    Google Scholar 

  64. Mourjopoulos, J., Clarkson, P., Hammond, J.: A comparative study of least-squares and homomorphic techniques for the inversion of mixed phase signals. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 7, pp. 1858–1861 (1982)

    Google Scholar 

  65. Mourjopoulos, J., Paraskevas, M.A.: Pole and zero modeling of room transfer functions. J. Sound Vib. 146(2), 281–302 (1991)

    Article  Google Scholar 

  66. Mourjopoulos, J.N.: Digital equalization of room acoustics. J. Audio Eng. Soc. 42(11), 884–900 (1994)

    Google Scholar 

  67. Nakatani, T., Miyoshi, M., Kinoshita, K.: Single-microphone blind dereverberation. In: J. Benesty, S. Makino, J. Chen (eds.) Speech Enhancement, 1 edn. Springer Verlag (2005)

    Google Scholar 

  68. Neely, S.T., Allen, J.B.: Invertibility of a room impulse response. J. Acoust. Soc. Am. 66(1), 165–169 (1979)

    Article  Google Scholar 

  69. Nelson, P.A., Orduña-Brustamante, F., Hamada, H.: Inverse filter design and equalization zones in multichannel sound reproduction. IEEE Trans. Speech Audio Process. 3(3), 185–192 (1995)

    Article  Google Scholar 

  70. Nishiura, T., Nakanura, S., Shikano, K.: Speech enhancement by multiple beamforming with reflection signal equalization. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 1, pp. 189–192 (2001)

    Google Scholar 

  71. Omologo, M., Svazier, P., Matassoni, M.: Environmental conditions and acoustic transduction in hands-free speech recognition. Speech Communication 25(1), 75–95 (1998)

    Article  Google Scholar 

  72. Oppenheim, A.V., Schafer, R.W.: Digital signal processing, 1 edn. Prentice Hall (1975)

    Google Scholar 

  73. Oppenheim, A.V., Schafer, R.W., Stockham, T.G.: Nonlinear filtering of multiplied and convolved signals. IEEE Trans. Audio Electroacoust. AU-16(3), 437–466 (1968)

    Article  Google Scholar 

  74. Paatero, T.: Modeling of long and complex responses using Kautz filters and time-domain partitions. In: Proc. European Signal Processing Conf. (EUSIPCO), pp. 313–316. Vienna, Austria (2004)

    Google Scholar 

  75. Petropulu, A.P., Nikias, C.L.: Blind deconvolution using signal reconstruction from partial higher order cepstral information. IEEE Trans. Signal Process. 41(6), 2088–2095 (1993)

    Article  MATH  Google Scholar 

  76. Plato: The republic. Penguin Books Ltd (2003)

    Google Scholar 

  77. Polycom: Polycom communicator. [Online] (2006). URL http://www.polycom.com/

    Google Scholar 

  78. Radlovi´c, B.D., Kennedy, R.A.: Nonminimum-phase equalization and its subjective importance in room acoustics. IEEE Trans. Speech Audio Process. 8(6), 728–737 (2000)

    Article  Google Scholar 

  79. Radlovi´c, B.D., Williamson, R.C., Kennedy, R.A.: Equalization in an acoustic reverberant environment: Robustness results. IEEE Trans. Acoust., Speech, Signal Process. 8(3), 311–319 (2000)

    Google Scholar 

  80. Rayleigh, J.W.S.: The theory of sound. Dover Publications (1976)

    Google Scholar 

  81. Sabine, W.C.: Collected papers on acoustics. Dover Publications (1964)

    Google Scholar 

  82. Schmidt, G.: Applications of acoustic echo control – an overview. In: Proc. European Signal Processing Conf. (EUSIPCO), pp. 9–16. Vienna, Austria (2004)

    Google Scholar 

  83. Schroeder, M.R.: Statistical parameters of the frequency response curves of large rooms. J. Audio Eng. Soc. 35(5), 299–305 (1987)

    MathSciNet  Google Scholar 

  84. Subramaniam, S., Petropulu, A.P., Wendt, C.: Cepstrum-based deconvolution for speech dereverberation. IEEE Trans. Acoust., Speech, Signal Process. 4(5), 392–396 (1996)

    Google Scholar 

  85. Talantzis, F., Ward, D.B.: Robustness of multi-channel equalization in an acoustic reverberant environment. J. Acoust. Soc. Am. 114(2), 833–841 (2003)

    Article  Google Scholar 

  86. Thomas, M.R.P., Gaubitch, N.D., Gudnason, J., Naylor, P.A.: A practical multichannel dereverberation algorithm using multichannel DYPSA and spatiotemporal averaging. In: Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. New Paltz, NY (2007)

    Google Scholar 

  87. Tohyama, M., Lyon, R.H., Koike, T.: Source waveform recovery in a reverberant space by cepstrum dereverberation. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 1, pp. 157–160 (1993)

    Google Scholar 

  88. Triki, M., Slock, D.T.M.: Delay-and-predict equalization for blind speech dereverberation. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP). Toulouse, France (2006)

    Google Scholar 

  89. VanVeen, B.D., Buckley, K.M.: Beamforming: a versatile approach to spatial filtering. IEEE Signal Process. Mag. 5(2), 4–24 (1988)

    Google Scholar 

  90. Waller, S.J.: Sound and rock art. Nature 363 (1993)

    Google Scholar 

  91. Waller, S.J.: Psychoacoustic influences of the echoing environments of prehistoric art. J. Acoust. Soc. Am. 112 (2002)

    Google Scholar 

  92. Ward, D.B.: On the performance of acoustic crosstalk cancellation in a reverberant environment. J. Acoust. Soc. Am. 110(2), 1195–1198 (2001)

    Article  Google Scholar 

  93. Wen, J.Y.C., Gaubitch, N.D., Habets, E.A.P., Myatt, T., Naylor, P.A.: Evaluation of speech dereverberation algorithms using the MARDY database. In: Proc. Int. Workshop Acoust. Echo Noise Control (IWAENC). Paris, France (2006)

    Google Scholar 

  94. Wu, M., Wang, D.: A two-stage algorithm for one-microphone reverberant speech enhancement. IEEE Trans. Audio, Speech, Lang. Process. 14(3), 774–784 (2006)

    Article  Google Scholar 

  95. Xu, G., Liu, H., Tong, L., Kailath, T.: A least-squares approach to blind channel identification. IEEE Trans. Signal Process. 43(12), 2982–2993 (1995)

    Article  Google Scholar 

  96. Yamada, K., Wang, J., Itakura, F.: Recovering of broad band reverberant speech signal by subband MINT method. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 969–972 (1991)

    Google Scholar 

  97. Yegnanarayana, B., Prasanna, S.R.M., Rao, K.S.: Speech enhancement using excitation source information. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), vol. 1, pp. 541–544 (2002)

    Google Scholar 

  98. Yegnanarayana, B., Satyanarayana, P.: Enhancement of reverberant speech using LP residual signal. IEEE Trans. Acoust., Speech, Signal Process. 8(3), 267–281 (2000)

    Google Scholar 

  99. Zhang, W., Gaubitch, N.D., Naylor, P.A.: Computationally efficient equalization of room impulse responses robust to system estimation errors. In: Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP) (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Imperial College London, London, UK

    Patrick A. Naylor & Nikolay D. Gaubitch

Authors
  1. Patrick A. Naylor
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nikolay D. Gaubitch
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, SW7 2AZ, London, UK

    Patrick A. Naylor  & Nikolay D. Gaubitch  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag London Limited

About this chapter

Cite this chapter

Naylor, P., Gaubitch, N. (2010). Introduction. In: Naylor, P., Gaubitch, N. (eds) Speech Dereverberation. Signals and Commmunication Technology. Springer, London. https://doi.org/10.1007/978-1-84996-056-4_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-84996-056-4_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-055-7

  • Online ISBN: 978-1-84996-056-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation