This chapter presents low-distortion noise cancellers with their applications to communications and speech recognition. This classical technique, originally proposed by Widrow et al. in mid 70’s, is first reviewed from a view point of output-signal distortion to show that interference and crosstalk are the primary reasons. As a solution to the interference problem, a paired filter (PF) structure introduces an auxiliary adaptive filter for estimating a signal-to-noise ratio (SNR) that is used to control the coefficient-adaptation stepsize in the main adaptive filter. A small stepsize for high SNRs, when the desired signal seriously interferes the misadjustment, provides steady and accurate change of coefficients, leading to low-distortion. This PF structure is extended to more general cases in which crosstalk from the desired-signal source to the auxiliary microphone is not negligible. A cross-coupled paired filter (CCPF) structure and its generalized version are solutions that employ another set of paired filters. The generalized CCPF (GCCPF) is applied to speech recognition in a human-robot communication scenario where improvement in distortion is successfully demonstrated by evaluations in the real environment. This robot had been demonstrated for six months at 2005 World Exposition in Aichi, Japan.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
M. J. Al-Kindi, J. Dunlop: A low distortion adaptive noise cancellation structure for real time applications, Proc. ICASSP ’87, 2153–2156, Apr. 1987.
S. F. Boll: Suppression of acoustic noise in speech using spectral subtraction, IEEE Trans. Acoust., Speech, Signal Processing, ASSP-27(2), 113–120, Apr. 1979.
S. F. Boll, D. C. Pulsipher: Suppression of acoustic noise in speech using two microphone adaptive noise cancellation, IEEE Trans. Acoust., Speech, and Signal Processing, ASSP-28, 752–753, 1980.
M. Brandstein, D. Ward (eds.): Microphone Arrays, Berlin, Germany: Springer, 2001.
J. Dunlop, M. J. Al-Kindi, L. E. Virr: Application of adaptive noise cancelling to diver voice communications, Proc. ICASSP ’87, 1708–1711, Apr. 1987.
Y. Ephraim, D. Malah: Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator, IEEE Trans. Acoust., Speech, Signal Processing, ASSP-32(6), 1109–1121, Dec. 1984.
Y. Fujita: Personal robot PaPeRo, J. of Robotics and Mechatronics, 14(1), Jan. 2002.
W. A. Gardner, B. G. Agee: Two-stage adaptive noise cancellation for intermittent-signal applications, IEEE Trans. IT, IT-26(6), 746–750, Nov. 1980.
G. C. Goodwin, K. S. Sin: Adaptive Filtering, Prediction and Control, Englewood Cliffs, NJ, USA: Prentice-Hall, 1985.
W. A. Harrison, J. S. Lim, E. Singer: A new application of adaptive noise cancellation, IEEE Trans. Acoust., Speech, and Signal Processing, ASSP-34, 21–27, 1986.
S. Ikeda, A. Sugiyama: An adaptive noise canceller with low signal-distortion for speech codecs, IEEE Trans. Sig. Proc., 665–674, Mar. 1999.
S. Ikeda, A. Sugiyama: An adaptive noise canceller with low signal-distortion in the presence of crosstalk, IEICE Trans. Fund, 1517–1525, Aug. 1999.
H. Kubota, T. Furukawa, H. Itakura: Pre-processed noise canceller design and its performance, IEICE Trans. Fund., J69-A(5), 584–591, May 1986 (in Japanese).
G. Mirchandani, R. L. Zinser, J. B. Evans: A new adaptive noise cancellation scheme in the presence of crosstalk, IEEE Trans. CAS-II, 681–694, Oct. 1992.
V. Parsa, P. A. Parker, R. N. Scott: Performance analysis of a crosstalk resistant adaptive noise canceller, IEEE Trans. Circuits and Systems, 43, 473-482, 1996.
M. Sato, A. Sugiyama, S. Ohnaka: An adaptive noise canceler with low signal-distortion based on variable stepsize subfilters for human-robot communication, IEICE Trans. Fund., E88-A(8), 2055–2061, Aug. 2005.
M. Sato, T. Iwasawa, A. Sugiyama: A noise-robust speech recognition on a compact speech dialogue module, Proc. SIG AI-Challenge 2007, Nov. 2007 (in Japanese).
A. Sugiyama, M. N. S. Swamy, E. I. Plotkin: A fast convergence algorithm for adaptive FIR filters, Proc. ICASSP ’89, 892–895, 1989.
A. Sugiyama, M. Sato: Robust speech recognition in noisy environment for robot applications, J. of Acoust. Soc. Japan, 63(1), 47–53, Jan. 2007 (in Japanese).
J.-M. Valin, J. Rouat, F. Michaud: Enhanced robot audition based on microphone array source separation with post-filter, Proc. ICRSJ 2004, 3(28), 2123–2128, Oct. 2004.
T. Watanabe: Problems in the design of a speech recognition system and their solution, Trans., J.79-D-II(12), 2022–2031, Dec. 1996 (in Japanese).
B. Widrow, J. R. Glover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong, Jr., R. C. Goodlin: Adaptive noise cancelling: principles and applications, Proc. IEEE, 63(12), 1692–1716, 1975.
R. L. Zinser, G. Mirchandani, J. B. Evans: Some experimental and theoretical results using a new adaptive filter structure for noise cancellation in the presence of crosstalk, Proc. ICASSP ’85, 1253–1256, Mar. 1985.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Sugiyama, A. (2008). Low Distortion Noise Cancellers – Revival of a Classical Technique. 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_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-70602-1_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70601-4
Online ISBN: 978-3-540-70602-1
eBook Packages: EngineeringEngineering (R0)