Abstract
The convenience and the ease of use provided by hands-free operation of speech communication devices mean that speech enhancement schemes are becoming indispensable. In this chapter, two subband adaptive microphone array schemes are presented, which aim to provide good speech enhancement capability in poor signal to noise ratio situations. The basic commonality of the adaptive microphone array schemes is that they approximate the Wiener solution in an adaptive manner as new data comes in. Furthermore, both schemes include a quadratic constraint to prevent the trivial zero solution of the weights and to avoid suppression of the source of interest. The constraint is included to provide robustness against model mismatch and good spatial capture of the target signal. Furthermore, by using a subband structure the processing allows a time-frequency operation for each channel. As such, both schemes utilize the spatial, spectral, and temporal domains in an efficient and concise manner allowing a computational effective processing while maintaining high performance speech enhancement. Evaluations on the same data set, gathered from a car, show that the proposed schemes achieve good noise suppression up to 20 dB while experiencing very low levels of speech distortion.
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
Y. Grenier, “A microphone array for car environment,” Speech Communication, vol. 12, pp. 25–39, Dec. 1993.
S. Nordholm, I. Claesson, and B. Bengtsson, “Adaptive array noise suppression of handsfree speaker input in cars,” IEEE Trans. on Vehicular Technology, vol. 42, pp. 514–518, Nov. 1993.
N. Grbić, S. Nordholm, and A. Johansson, “Speech enhancement for handsfree terminals,” in Proc. IEEE Int. Sym. on Image and Signal Process. and Analysis, 2001, pp. 435–440.
N. Grbić and S. Nordholm, “Soft constrained subband beamforming for handsfree speech enhancement,” in Proc. IEEE ICASSP, 2002, vol. 1, pp. 885–888.
E. Jan and J. Flanagan, “Microphone arrays for speech processing,” in Proc. IEEE Int. Sym. on Signals, Systems, and Electronics, 1995, pp. 373–376.
M. Brandstein and D. B. Ward, Editors, Microphone Arrays: Signal Processing Techniques and Applications, Ch. 3, pp. 39–60, Springer-Verlag, 2001.
B. D. Van Veen and K. M. Buckley, “Beamforming: a versatile approach to spatial filtering,” IEEE Acoust., Speech and Signal Process. Magazine, vol. 5, pp. 4–24, Apr. 1988.
H. Q. Dam, S. Nordholm, N. Grbic, and H. H. Dam, “Speech enhancement employing adaptive beamformer with recursively updated soft constraints,” in Proc. IWAENC, 2003, pp. 307–310.
S. Y. Low, S. Nordholm, and N Grbić, “Subband generalized sidelobe canceller-a constrained region approach,” in Proc. IEEE Int. Workshop on Apps. of Signal Process. to Audio and Acoust., 2003, pp. 41–44.
H. Q. Dam, S. Y. Low, S. Nordholm, and H. H. Dam, “Adaptive microphone array with noise statistics updates,” in Proc. IEEE Int. Sym. on Circuits and Systems, 2004, vol. 3, pp. 433–436.
O. Hoshuyama, A. Sugiyama, and A. Hirano, “A robust adaptive beamformer for microphone arrays with a blocking matrix using constrained adaptive filters,” IEEE Trans. on Signal Process., vol. 47, pp. 2677–2684, June 1999.
I. Claesson and S. Nordholm, “A spatial filtering approach to robust beamforming,” IEEE Trans. on Antennas and Propagation, vol. 40, pp. 1093–1096, Sept. 1992.
S. Nordholm, I. Claesson, and M. Dahl, “Adaptive microphone array employing calibration signals: analytical evaluation,” IEEE Trans. on Speech and Audio Process., vol. 7, pp. 241–252, May 1999.
M. Dahl and I. Claesson, “Acoustic noise and echo cancelling with microphone array,” IEEE Trans. on Speech and Audio Process., vol. 48, pp. 1518–1526, Sept. 1999.
N. Grbić, S. Nordholm, and A. Cantoni, “Optimal FIR subband beamforming for speech enhancement in multipath environments,” IEEE Signal Process. Letters, vol. 10, pp. 335–338, Nov. 2003.
N. Grbić, S. Nordholm, and A. Cantoni, “Limits in FIR subband beamforming for spatially spread near-field speech sources,” in Proc. IEEE Int. Sym. on Circuits and Systems, 2003, vol. 2, pp. 516–519.
H. Q. Dam, S. Y. Low, H. H. Dam, and S. Nordholm, “Space constrained beamforming with source PSD updates,” in Proc. IEEE ICASSP, 2004, vol. 4, pp. 93–96.
J. M. de Haan, N. Grbić, I. Claesson, and S. Nordholm, “Filter bank design for subband adaptive microphone arrays,” IEEE Trans. on Speech and Audio Process., vol. 11, pp. 14–23, Jan. 2003.
K. F. C. Yiu, N. Grbić, S. Nordholm, and K. L. Teo, “Multicriteria design of oversampled uniform DFT filter banks,” IEEE Signal Process. Letters, vol. 11, pp. 541–544, June 2004.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Nordholm, S., Dam, H.Q., Grbić, N., Low, S.Y. (2005). Adaptive Microphone Array Employing Spatial Quadratic Soft Constraints and Spectral Shaping. In: Speech Enhancement. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27489-8_10
Download citation
DOI: https://doi.org/10.1007/3-540-27489-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24039-6
Online ISBN: 978-3-540-27489-6
eBook Packages: EngineeringEngineering (R0)