Skip to content

Advertisement

EURASIP Journal on Audio, Speech, and Music Processing

EURASIP Journal on Audio, Speech, and Music Processing Cover Image
  • Research Article
  • Open Access

Multimicrophone Speech Dereverberation: Experimental Validation

EURASIP Journal on Audio, Speech, and Music Processing20072007:051831

https://doi.org/10.1155/2007/51831

©  K. Eneman and M. Moonen. 2007

Received: 6 September 2006

Accepted: 10 April 2007

Published: 2 May 2007

Abstract

Dereverberation is required in various speech processing applications such as handsfree telephony and voice-controlled systems, especially when signals are applied that are recorded in a moderately or highly reverberant environment. In this paper, we compare a number of classical and more recently developed multimicrophone dereverberation algorithms, and validate the different algorithmic settings by means of two performance indices and a speech recognition system. It is found that some of the classical solutions obtain a moderate signal enhancement. More advanced subspace-based dereverberation techniques, on the other hand, fail to enhance the signals despite their high-computational load.

Keywords

AcousticsPerformance IndexClassical SolutionSpeech RecognitionExperimental Validation

[1234567891011121314151617181920212223242526272829303132]

Authors’ Affiliations

(1)
ExpORL, Department of Neurosciences, Katholieke Universiteit Leuven, Leuven, Belgium
(2)
GroupT Leuven Engineering School, Leuven, Belgium
(3)
SCD, Department of Electrical Engineering (ESAT), Faculty of Engineering, Katholieke Universiteit Leuven, Leuven, Belgium

References

  1. Bees D, Blostein M, Kabal P: Reverberant speech enhancement using cepstral processing. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '91), May 1991, Toronto, Ontario, Canada 2: 977-980.Google Scholar
  2. Liu Q-G, Champagne B, Kabal P: A microphone array processing technique for speech enhancement in a reverberant space. Speech Communication 1996,18(4):317-334. 10.1016/0167-6393(96)00011-8View ArticleGoogle Scholar
  3. Oppenheim A, Schafer R: Digital Signal Processing. Prentice-Hall, Englewood Cliffs, NJ, USA; 1975. chapter 10MATHGoogle Scholar
  4. Petropulu AP, Subramaniam S: Cepstrum based deconvolution for speech dereverberation. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '94), April 1994, Adelaide, Australia 1: 9-12.Google Scholar
  5. Allen JB, Berkley DA, Blauert J: Multimicrophone signal-processing technique to remove room reverberation from speech signals. The Journal of the Acoustical Society of America 1977,62(4):912-915. 10.1121/1.381621View ArticleGoogle Scholar
  6. Wittkop T, Hohmann V: Strategy-selective noise reduction for binaural digital hearing aids. Speech Communication 2003,39(1-2):111-138. 10.1016/S0167-6393(02)00062-6View ArticleMATHGoogle Scholar
  7. Miyoshi M, Kaneda Y: Inverse filtering of room acoustics. IEEE Transactions on Acoustics, Speech, and Signal Processing 1988,36(2):145-152. 10.1109/29.1509View ArticleGoogle Scholar
  8. Nelson PA, Orduna-Bustamante F, Hamada H: Inverse filter design and equalization zones in multichannel sound reproduction. IEEE Transactions on Speech and Audio Processing 1995,3(3):185-192. 10.1109/89.388144View ArticleGoogle Scholar
  9. Grenier Y: A microphone array for car environments. Speech Communication 1993,12(1):25-39. 10.1016/0167-6393(93)90016-EMathSciNetView ArticleGoogle Scholar
  10. Sydow C: Broadband beamforming for a microphone array. The Journal of the Acoustical Society of America 1994,96(2):845-849. 10.1121/1.410323View ArticleGoogle Scholar
  11. van Veen BD, Buckley KM: Beamforming: a versatile approach to spatial filtering. IEEE ASSP Magazine 1988,5(2):4-24.View ArticleGoogle Scholar
  12. Affes S, Grenier Y: A signal subspace tracking algorithm for microphone array processing of speech. IEEE Transactions on Speech and Audio Processing 1997,5(5):425-437. 10.1109/89.622565View ArticleGoogle Scholar
  13. Moulines E, Duhamel P, Cardoso J-F, Mayrargue S: Subspace methods for the blind identification of multichannel FIR filters. IEEE Transactions on Signal Processing 1995,43(2):516-525. 10.1109/78.348133View ArticleGoogle Scholar
  14. van der Veen A-J, Talwar S, Paulraj A: Blind identification of FIR channels carrying multiple finite alphabet signals. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '95), May 1995, Detroit, Mich, USA 2: 1213-1216.Google Scholar
  15. Gannot S, Moonen M: Subspace methods for multi-microphone speech dereverberation. Proceedings of the 7th IEEE/EURASIP International Workshop on Acoustic Echo and Noise Control (IWAENC '01), September 2001, Darmstadt, Germany 47-50.Google Scholar
  16. Kuttruff H: Room Acoustics. 2nd edition. Applied Science Publishers, Essex, England; 1979.Google Scholar
  17. Johnson D, Dudgeon D: Array Signal Processing. Prentice-Hall, Englewood Cliffs, NJ, USA; 1993.MATHGoogle Scholar
  18. van Gerven D, van Compernolle S, Wauters P, Verstraeten W, Eneman K, Delaet K: Multiple beam broadband beamforming: filter design and real-time implementation. Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA '95), October 1995, New Paltz, NY, USA 173-176.Google Scholar
  19. Giannakis GB, Halford SD: Blind fractionally spaced equalization of noisy FIR channels: direct and adaptive solutions. IEEE Transactions on Signal Processing 1997,45(9):2277-2292. 10.1109/78.622950View ArticleGoogle Scholar
  20. Eneman K, Moonen M: Ambiguity elimination in frequency-domain subspace identification. In Internal Report ESAT-SCD 06.151. Katholieke Universiteit Leuven, Leuven, Belgium; 2007:12. https://gilbert.med.kuleuven.be/~koen/reports/06-151.pdfGoogle Scholar
  21. Eneman K, Moonen M: DFT modulated filter bank design for oversampled subband systems. Signal Processing 2001,81(9):1947-1973. 10.1016/S0165-1684(01)00084-6View ArticleMATHGoogle Scholar
  22. Vaidyanathan P: Multirate Systems and Filter Banks. Prentice-Hall, Englewood Cliffs, NJ, USA; 1993.MATHGoogle Scholar
  23. Rahbar K, Reilly JP, Manton JH: A frequency domain approach to blind identification of MIMO FIR systems driven by quasi-stationary signals. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '02), May 2002, Orlando, Fla, USA 2: 1717-1720.Google Scholar
  24. Eneman K, Moonen M: Hybrid subband/frequency-domain adaptive systems. Signal Processing 2001,81(1):117-136. 10.1016/S0165-1684(00)00197-3View ArticleMATHGoogle Scholar
  25. Doclo S, Moonen M: Combined frequency-domain dereverberation and noise reduction technique for multi-microphone speech enhancement. Proceedings of the 7th IEEE/EURASIP International Workshop on Acoustic Echo and Noise Control (IWAENC '01), September 2001, Darmstadt, Germany 31-34.Google Scholar
  26. Allen JB, Berkley DA: Image method for efficiently simulating small-room acoustics. The Journal of the Acoustical Society of America 1979,65(4):943-950. 10.1121/1.382599View ArticleGoogle Scholar
  27. Eneman K, Duchateau J, Moonen M, van Compernolle D, van Hamme H: Assessment of dereverberation algorithms for large vocabulary speech recognition systems. Proceedings of the 8th European Conference on Speech Communication and Technology (Eurospeech '03), September 2003, Geneva, Switzerland 2689-2692.Google Scholar
  28. Duchateau J, Demuynck K, van Compernolle D, Wambacq P: Class definition in discriminant feature analysis. Proceedings of the 7th European Conference on Speech Communication and Technology (Eurospeech '01), September 2001, Aalborg, Denmark 3: 1621-1624.Google Scholar
  29. Demuynck K, Duchateau J, van Compernolle D, Wambacq P: Improved feature decorrelation for HMM-based speech recognition. Proceedings of the 5th International Conference on Spoken Language Processing (ICSLP '98), November-December 1998, Sydney, Australia 7: 2907-2910.Google Scholar
  30. Duchateau J, Demuynck K, van Compernolle D: Fast and accurate acoustic modelling with semi-continuous HMMs. Speech Communication 1998,24(1):5-17. 10.1016/S0167-6393(98)00002-8View ArticleGoogle Scholar
  31. Demuynck K, Duchateau J, van Compernolle D, Wambacq P: An efficient search space representation for large vocabulary continuous speech recognition. Speech Communication 2000,30(1):37-53. 10.1016/S0167-6393(99)00030-8View ArticleGoogle Scholar
  32. Bees D: Enhancement of acoustically reverberant speech using cepstral methods, Ph.D. thesis. McGill University, Montreal, Canada; 1990.Google Scholar

Copyright

© K. Eneman and M. Moonen. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement