Skip to main content

Dereverberation and Residual Echo Suppression in Noisy Environments

  • Chapter
Speech and Audio Processing in Adverse Environments

Hands-free devices, such as mobile phones, are often used in noisy and reverberant environments. Therefore, the received microphone signal contains not only the desired speech (commonly called near-end speech) signal, but also interferences such as reverberations of the desired source, background noise, and a far-end echo signal that results from a sound that is produced by the loudspeaker. These interferences degrade the fidelity and intelligibility of the near-end speech and decrease the performance of automatic speech recognition systems.

Acoustic echo cancellers are widely used to cancel the far-end echo. Postprocessors, employed in conjunction with acoustic echo cancellers, further enhance the near-end speech. Most post-processors that are described in the literature only suppress background noise and residual echo, i.e., echo which is not suppressed by the acoustic echo canceller. The intelligibility of the nearend speech also depends on the amount of reverberation. Dereverberation techniques have been developed to cancel or suppress reverberation. Recently, practically feasible spectral enhancement techniques to suppress reverberation have emerged that can be incorporated into the post-processor.

After a short introduction, the problems encountered in a hands-free device are formulated. A general purpose post-filter is developed, which can be used to suppress non-stationary, as well as stationary, interferences. The problem of dereverberation of noisy speech signals is addressed by using the general purpose post-filter employed to suppress reverberation and background noise. Next, suppression of residual echo is discussed. Finally, a post-processor is developed for the joint suppression of reverberation, residual echo, and background noise. An experimental study demonstrates the beneficial use of the proposed post-processor for jointly reducing reverberation, residual echo, and background noise.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
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. A. J. Accardi, R. V. Cox: A modular approach to speech enhancement with an application to speech coding, Proc. ICASSP ’99, 1, 201–204, 1999.

    Google Scholar 

  2. F. Aigner, M. J. O. Strutt: On a physiological effect of several sources of sound on the ear and its consequences in architectural acoustics, JASA, 6(3), 155–159, 1935.

    Google Scholar 

  3. J. B. Allen, L. Radiner: A unified approach to short-time fourier analysis and synthesis, Proc. of the IEEE, 65(11), 1558–1564, 1977.

    Article  Google Scholar 

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

    Google Scholar 

  5. J. B. Allen: Effects of small room reverberation on subjective preference, JASA, 71, 1–5, 1982.

    Google Scholar 

  6. P. Bloom, G. Cain: Evaluation of two input speech dereverberation techniques, Proc. ICASSP ’82, 1, 164–167, 1982.

    Google Scholar 

  7. R. Le Bouquin Jeannès, P. Scalart, G. Faucon, C. Beaugeant: Combined noise and echo reduction in hands-free systems: a survey, IEEE Trans. Speech Audio Processing, 9(8), 808–820, 2001.

    Article  Google Scholar 

  8. C. Breining, P. Dreiseitel, E. Hänsler, A. Mader, B. Nitsch, H. Puder, T. Schertler, G. Schmidt, J. Tilp: Acoustic echo control – an application of very-high-order adaptive filters, IEEE Signal Processing Mag., 16(4), 42–69, 1999.

    Article  Google Scholar 

  9. I. Cohen, B. Berdugo: Noise estimation by minima controlled recursive averaging for robust speech enhancement, IEEE Signal Processing Lett., 9(1), 12–15, Jan. 2002.

    Article  Google Scholar 

  10. I. Cohen: Optimal speech enhancement under signal presence uncertainty using log-spectral amplitude estimator, IEEE Signal Processing Lett., 9(4), 113–116, Apr. 2002.

    Article  Google Scholar 

  11. I. Cohen: Noise spectrum estimation in adverse environments: Improved minima controlled recursive averaging, IEEE Trans. Speech Audio Processing, 11(5), 466–475, Sept. 2003.

    Article  Google Scholar 

  12. I. Cohen: Relaxed statistical model for speech enhancement and a priori SNR estimation, IEEE Trans. Speech Audio Processing, 13(5), 870–881, Sept. 2005.

    Article  Google Scholar 

  13. T. J. Cox, F. Li, P. Darlington: Extracting room reverberation time from speech using artificial neural networks, Journal of the Audio Engineering Society, 49(4), 219–230, 2001.

    Google Scholar 

  14. R. E. Crochiere, L. R. Rabiner: Multirate Digital Signal Processing, Englewood Cliffs, NJ, USA: Prentice-Hall, 1983.

    Google Scholar 

  15. M. Delcroix, T. Hikichi, M. Miyoshi: Precise dereverberation using multichannel linear prediction, IEEE Trans. Audio, Speech, Language Processing, 15(2), 430–440, 2006.

    Article  Google Scholar 

  16. J. R. Deller, J. G. Proakis, J. H. L. Hansen: Discrete-Time Processing of Speech Signals, New York, NY, USA: MacMillan, 1993.

    Google Scholar 

  17. M. Dörbecker, S. Ernst: Combination of two-channel spectral subtraction and adaptive Wiener post-filtering for noise reduction and dereverberation, Proc. EUSIPCO ’96, Triest, Italy, 1996.

    Google Scholar 

  18. G. Enzner: A Model-Based Optimum Filtering Approach to Acoustic Echo Control: Theory and Practice, Ph.D. thesis, RWTH Aachen University, Aachen, Germany: Wissenschaftsverlag Mainz, 2006.

    Google Scholar 

  19. Y. Ephraim, D. Malah: Speech enhancement using a minimum mean square error short-time spectral amplitude estimator, IEEE Trans. Acoust., Speech, Signal Processing, 32(6), 1109–1121, Dec. 1984.

    Article  Google Scholar 

  20. Y. Ephraim, D. Malah: Speech enhancement using a minimum mean square error log-spectral amplitude estimator, IEEE Trans. Acoust., Speech, Signal Processing, 33(2), 443–445, Apr. 1985.

    Article  Google Scholar 

  21. S. Gannot, M. Moonen: Subspace methods for multimicrophone speech dereverberation, EURASIP Journal on Applied Signal Processing, 11, 1074–1090, 2003.

    Google Scholar 

  22. T. Gänsler, J. Benesty: The fast normalized cross-correlation double-talk detector, Signal Processing, 86, 1124–1139, June 2006.

    Article  MATH  Google Scholar 

  23. N. D. Gaubitch, P. A. Naylor, D. Ward: On the use of linear prediction for dereverberation of speech, Proc. IWAENC ’03, 99–102, Kyoto, Japan, 2003.

    Google Scholar 

  24. Y. Grenier, M. Xu, J. Prado, D. Liebenguth: Real-time implementation of an acoustic antenna for audio-conference, Proc. IWAENC ’89, Berlin, Germany, Sept. 1989.

    Google Scholar 

  25. S. Griebel, M. Brandstein: Wavelet transform extrema clustering for multi-channel speech deverberation, Proc. WASPAA ’99, 1999.

    Google Scholar 

  26. M. Gürelli, C. Nikias: EVAM: an eigenvector-based algorithm for multichannel blind deconvolution of input colored signals, IEEE Trans. Signal Processing, 43(1), 134–149, 1995.

    Article  Google Scholar 

  27. S. Gustafsson, R. Martin, P. Vary: Combined acoustic echo control and noise reduction for hands-free telephony, Signal Processing, 64, 21–32, 1998.

    Article  MATH  Google Scholar 

  28. S. Gustafsson, R. Martin, P. Jax, P. Vary: A psychoacoustic approach to combined acoustic echo cancellation and noise reduction, IEEE Trans. Speech Audio Processing, 10(5), 245–256, 2002.

    Article  Google Scholar 

  29. E. A. P. Habets: Multi-channel speech dereverberation based on a statistical model of late reverberation, Proc. ICASSP ’05, 173–176, Philadelphia, USA, Mar. 2005.

    Google Scholar 

  30. E. A. P. Habets, I. Cohen, S. Gannot: MMSE log spectral amplitude estimator for multiple interferences, Proc. IWAENC ’06, 1–4, Paris, France, Sept. 2006.

    Google Scholar 

  31. E.A.P. Habets: Single- and Multi-Microphone Speech Dereverberation using Spectral Enhancement, Ph.D. Thesis, Technische Universiteit Eindhoven, June 2007.

    Google Scholar 

  32. E. Hänsler: The hands-free telephone probleman annotated bibliography, Signal Processing, 27(3), 259–271, 1992.

    Article  Google Scholar 

  33. E. Hänsler, G. Schmidt: Hands-free telephones – joint control of echo cancellation and postfiltering, Signal Processing, 80, 2295–2305, 2000.

    Article  MATH  Google Scholar 

  34. E. Hänsler, G. Schmidt: Acoustic Echo and Noise Control: A Practical Approach, Hoboken, NJ, USA: Wiley-IEEE Press, 2004.

    Book  Google Scholar 

  35. S. Haykin: Blind Deconvolution, fourth ed., Englewood Cliffs, NJ, USA: Prentice-Hall, 1994.

    Google Scholar 

  36. J. Hopgood: Nonstationary Signal Processing with Application to Reverberation Cancellation in Acoustic Environments, Ph.D. thesis, Cambridge University, 2001.

    Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  38. J. J. Jetzt: Critical distance measurement of rooms from the sound energy spectral response, JASA,65(5), 1204–1211, 1979.

    Google Scholar 

  39. J.-M. Jot, L. Cerveau, O. Warusfel: Analysis and synthesis of room reverberation based on a statistical time-frequency model, Audio Engineering Society, 103th Convention, Aug. 1997.

    Google Scholar 

  40. H. Kuttruff: Room Acoustics, fourth ed., London, GB: Spon Press, 2000.

    Google Scholar 

  41. K. Lebart, J. M. Boucher, P. N. Denbigh: A new method based on spectral subtraction for speech dereverberation, Acta Acoustica, 87(3), 359–366, 2001.

    Google Scholar 

  42. R. Martin, P. Vary: Combined acoustic echo cancellation, dereverberation and noise reduction: a two microphone approach, Annales des Telecommunications, 49(7–8), 429–438, 1994.

    Google Scholar 

  43. R. Martin: Noise power spectral density estimation based on optimal smoothing and minimum statistics, IEEE Trans. Speech Audio Processing, 9(5), 504–512, 2001.

    Article  Google Scholar 

  44. M. Miyoshi, Y. Kaneda: Inverse filtering of room acoustics, IEEE Trans. Speech Audio Processing, 36(2), 145–152, 1988.

    Google Scholar 

  45. V. Myllylä: Residual echo filter for enhanced acoustic echo control, Signal Processing, 86(6), 1193–1205, June 2006.

    Article  MATH  Google Scholar 

  46. A. K. Nábělek, T. R. Letowski, F. M. Tucker: Reverberant overlap- and self-masking in consonant identification, JASA, 86(4), 1259–1265, 1989.

    Google Scholar 

  47. P. A. Naylor, N.D. Gaubitch: Speech dereverberation, Proc. IWAENC ’05, 2005.

    Google Scholar 

  48. P. M. Peterson: Simulating the response of multiple microphones to a single acoustic source in a reverberant room, JASA, 80(5), 1527–1529, Nov. 1986.

    Google Scholar 

  49. J. D. Polack: La transmission de l’énergie sonore dans les salles, Thèse de doctorat d’etat, Université du Maine, La mans, 1988.

    Google Scholar 

  50. J. D. Polack: Playing billiards in the concert hall: the mathematical foundations of geometrical room acoustics, Applied Acoustics, 38(2), 235–244, 1993.

    Article  Google Scholar 

  51. B. D. Radlović, R. Williamson, R. Kennedy: Equalization in an acoustic reverberant environment: robustness results, IEEE Trans. Speech Audio Processing, 8(3), 311–319, 2000.

    Article  Google Scholar 

  52. R. Ratnam, D. L. Jones, B. C. Wheeler, W. D. O’Brien Jr., C. R. Lansing, A. S. Feng: Blind estimation of reverberation time, JASA, 114(5), 2877–2892, Nov. 2003.

    Google Scholar 

  53. W. C. Sabine: Collected Papers on Acoustics (Originally 1921), Los Altos, CA, USA: Peninsula Publishing, 1993.

    Google Scholar 

  54. G. Schmidt: Applications of acoustic echo control - an overview, Proc. EUSIPCO ’04, Vienna, Austria, 2004.

    Google Scholar 

  55. M. R. Schroeder: Statistical parameters of the frequency response curves of large rooms, Journal of the Audio Engineering Society, 35, 299–306, 1954.

    MathSciNet  Google Scholar 

  56. M. R. Schroeder: Frequency correlation functions of frequency responses in rooms, JASA, 34(12), 1819–1823, 1962.

    Google Scholar 

  57. M. R. Schroeder: Integrated-impulse method measuring sound decay without using impulses, JASA, 66(2), 497–500, 1979.

    Google Scholar 

  58. F. Talantzis, D. B. Ward: Robustness of multichannel equalization in an acoustic reverberant environment, JASA, 114(2), 833–841, 2003.

    Google Scholar 

  59. M. Triki, D. T. M. Slock: Delay and predict equalization for blind speech dereverberation, Proc. ICASSP ’06, 5, 97–100, Toulouse, France, May 2006.

    Google Scholar 

  60. V. Turbin, A. Gilloire, P. Scalart: Comparison of three post-filtering algorithms for residual acoustic echo reduction, Proc. ICASSP ’97, 1, 307–310, 1997.

    Google Scholar 

  61. A. Varga, H. J. M. Steeneken: Assessment for automatic speech recognition: II. NOISEX-92: a database and an experiment to study the effect of additive noise on speech recognition systems, Speech Communication, 12, 247–251, July 1993.

    Article  Google Scholar 

  62. J. Y. C. Wen, N. D. Gaubitch, E. A. P. Habets, T. Myatt, P. A. Naylor: Evaluation of speech dereverberation algorithms using the MARDY database, Proc. IWAENC ’06, 1–4, Paris, France, Sept. 2006.

    Google Scholar 

  63. M. Xu, Y.Grenier: Acoustic echo cancellation by adaptive antenna, Proc. IWAENC ’89, Berlin, Germany, Sept. 1989.

    Google Scholar 

  64. H. Yasukawa: An acoustic echo canceller with sub-band noise cancelling, IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, E75-A(11), 1516–1523, 1992.

    Google Scholar 

  65. B. Yegnanarayana, P. S. Murthy: Enhancement of reverberant speech using LP residual signal, IEEE Trans. Speech Audio Processing, 8(3), 267–281, 2000.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Habets, E.A.P., Gannot, S., Cohen, I. (2008). Dereverberation and Residual Echo Suppression in Noisy Environments. In: Hänsler, E., Schmidt, G. (eds) Speech and Audio Processing in Adverse Environments. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70602-1_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-70602-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70601-4

  • Online ISBN: 978-3-540-70602-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics