한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
권호 표지
DOI QR코드

DOI QR Code

음향반향제거기에서 기하학적 개념의 BSS를 이용한 동시통화 제어

Double-talk Control using Blind Signal Separation based on Geometric Concept in Acoustic Echo Canceller

  • 이행우 (남서울대학교 정보통신공학과)
  • 투고 : 2016.07.01
  • 심사 : 2017.06.16
  • 발행 : 2017.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문은 기하학적 개념에 기반한 암묵신호분리를 이용하여 동시통화문제를 제어하는 음향반향제거기에 관한 것이다. 음향반향제거기는 동시통화 구간에서 성능이 저하되거나 발산하게 된다. 따라서 혼합된 마이크 입력신호로부터 근단화자신호를 분리해서 동시통화상태를 검출하기 위하여 암묵신호분리기술을 이용한다. 암묵신호분리는 미지의 입력신호들로부터 기하학적 개념에 기반하여 변형과 회전의 두 단계를 거쳐 근단화자신호를 추정해낸다. 컴퓨터 시뮬레이션을 통하여 이 음향반향제거기의 성능을 검증하였다. 동시통화 구간에서는 반향제거필터의 계수가 발산하는 것을 방지하기 위하여 계수 갱신작업을 중지하도록 하였다. 시뮬레이션 결과, 이 방법을 사용한 음향반향제거기는 암묵신호분리의 빠른 수렴속도로 인해 동시통화의 유무에 상관없이 안전하게 동작함을 확인하였다.

This paper describes an acoustic echo canceller with double-talk using BSS(: Blind Signal Separation) based on the geometric concept. The acoustic echo canceller may be deteriorated or diverged during the double-talk period. So we use the blind signal separation to detect the double talking by separating the near-end speech signal from the mixed microphone signal. In the closed reverberation environment, the blind signal separation extracts the near-end signal from unknown signals with the transformation and rotation based on the geometric concept. By this method, the acoustic echo canceller operates irrespective of double-talking. We verified performances of the proposed acoustic echo canceller by computer simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods thoroughly, and operates stably in the normal state without diverging of coefficients after ending the double-talking.

키워드

참고문헌

  1. S. Minami and T. Kawasaki, "A Double Talk Detection Method for an Echo Canceller," ICC(:International Conference on Communications) '85, Chicago, USA, Jun. 1985, pp.1492-1497.
  2. H. Ye and B. Wu, "A New Double-Talk Detection Algorithm Based on the Orthogonality Theorem," IEEE Trans. on Comm., vol.39, no.11, Nov. 1991, pp.1542- 1545. https://doi.org/10.1109/26.111430
  3. W. Hsu, F. Chui, and D. Hodges, "An Acoustic Echo Canceler," IEEE J. of Solid-state Circuits, vol.24, no.6, Dec. 1989, pp.1639-1646. https://doi.org/10.1109/4.45000
  4. A. Bell and T. Sejnowski, "An Information Maximization Approach to Blind Separation and Blind Deconvolution," Neural Computation, vol.7, no.6, 1995, pp.1129-1159. https://doi.org/10.1162/neco.1995.7.6.1129
  5. K. Torkkola, "Blind Separation of Convolved Sources Based on Information Maximization," Neural Networks for Signal Processing, IEEE Signal Processing Society Workshop, Corfu, Greece, Jun. 1996.
  6. H. Saruwatari, T. Kawamura, and K. Shikano, "Blind Source Separation for Speech Based on Fast Convergence Algorithm with ICA and Beamforming," Proceedings of the Eurospeech 2001, Aalborg, Denmark, Sep. 2001, pp.2603- 2606.
  7. P. Comon, "Independent component analysis, A new concept," Signal Processing, vol.36, no.3, 1994, pp.287-314. https://doi.org/10.1016/0165-1684(94)90029-9
  8. M. Kawamoto, K. Matsuoka, and N. Ohnishi, "A method of blind separation for convolved non-stationary signals," Neuro Computing, vol.22, no.1-3, 1998, pp.157-171.
  9. L. Parra and C. Spence, "Convolutive blind separation of non-stationary sources," IEEE Trans. Speech Audio Process., vol.8, no.3, 2000, pp.320-327. https://doi.org/10.1109/89.841214
  10. D. Schobben and P. Sommen, "A frequency domain blind signal separation method based on decorrelation," IEEE Trans. Signal Process., vol.50, no.8, 2002, pp.1855-1865. https://doi.org/10.1109/TSP.2002.800417
  11. E. Weinstein, M. Feder, and A. Oppenheim, "Multi-channel signal separation by decorrelation," IEEE Trans. Speech Audio Process., vol.1, no.4, 1993, pp.405-413. https://doi.org/10.1109/89.242486
  12. D. Yellin and E. Weinstein, "Multichannel signal separation: methods and analysis," IEEE Trans. Signal Process., vol.44, no.1, 1996, pp.106-118. https://doi.org/10.1109/78.482016
  13. C. Puntonet, A. Prieto, C. Jutten, M. Alvarez, and J. Ortega, "Separation of sources : A geometry-based procedure for reconstruction of n-valued signals," Signal Processing, vol.46, no.3, 1995, pp.267-284. https://doi.org/10.1016/0165-1684(95)00088-0
  14. C. Guntonet and A. Prieto, "Neural net approach for blind separation of sources based on geometric properties," Neuro Computing, vol.18, no.3, 1998, pp.141-164.