NOISE REDUCTION BASED ON CROSS TF ε-FILTER

Tomomi Abe, Mitsuharu Matsumoto, Shuji Hashimoto

2008

Abstract

A time-frequency ε-filter (TF ε-filter) is an advanced ε-filter applied to complex spectra along the time axis. It can reduce most kinds of noise while preserving a signal that varies frequently such as a speech signal. The filter design is simple and it can effectively reduce noise. It is applicable not only to small amplitude stationary noise but also to large amplitude nonstationary noise. However when we consider the noise that varies much frequently along the time axis, TF ε-filter cannot reduce noise without the signal distortion. When we consider the noise where the neighboring frequency bins have similar powers such as impulse noise, we can reduce the noise by using ε-filter applied to the complex spectra not along the time axis, but along the frequency axis. This paper introduces an advanced method for noise reduction that applies ε-filter to complex spectra not only along the time axis but also along the frequency axis labeled cross TF ε-filter. We conducted the experiments utilizing the sounds with stationary, nonstationary and natural noise.

References

  1. Abe, T., Matsumoto, M., and Hashimoto, S. (2007). A method of noise reduction for speech signals using component separating e-filters. In J. of the AcousticSociety America., volume 122, pages 2697-2705.
  2. Arakawa, K., Matsuura, K., Watabe, H., and Arakawa, Y. (2002). Noise reduction combining time-domain e- filter and time-frequency e-filter. In IEICE trans on Fundamentals., volume J85-A, pages 1059-1069.
  3. Boll, S. F. (1979). Suppression of acoustic noise in speech using spectral subtraction. In IEEE Trans. Acoust. Speech Signal Process., volume ASSP-27, pages 113- 120.
  4. Daniel, P., Ellis, W., and Weiss., R. (2006). Model-based monaural source separation using a vector-quantized phase-vocoder representation. In Proc. IEEE Int'l Conf. on Acoustics, Speech, and Signal Process. 2006.
  5. Fujimoto, M. and Ariki, Y. (2002). Speech recognition under noisy environments using speech signal estimation method based on kalman filter. In IEICE Trans. Information and Systems, volume J85-D-II, pages 1-11.
  6. Harashima, H., Odajima, K., Shishikui, Y., and Miyakawa, H. (1982). e-separating nonlinear digital filter and its applications. In IEICE trans on Fundamentals., volume J65-A, pages 297-303.
  7. Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. In Trans. of the ASME, volume 82, pages 35-45.
  8. Lim, J. S., Oppenheim, A. V., and Braida, L. (1978). Evaluation of an adaptive comb filtering method for enhancing speech degraded by white noise addition. In IEEE Trans. on Acoust. Speech Signal Process., volume ASSP-26, pages 419-423.
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Paper Citation


in Harvard Style

Abe T., Matsumoto M. and Hashimoto S. (2008). NOISE REDUCTION BASED ON CROSS TF ε-FILTER . In Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008) ISBN 978-989-8111-60-9, pages 105-112. DOI: 10.5220/0001935001050112


in Bibtex Style

@conference{sigmap08,
author={Tomomi Abe and Mitsuharu Matsumoto and Shuji Hashimoto},
title={NOISE REDUCTION BASED ON CROSS TF ε-FILTER},
booktitle={Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008)},
year={2008},
pages={105-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001935001050112},
isbn={978-989-8111-60-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008)
TI - NOISE REDUCTION BASED ON CROSS TF ε-FILTER
SN - 978-989-8111-60-9
AU - Abe T.
AU - Matsumoto M.
AU - Hashimoto S.
PY - 2008
SP - 105
EP - 112
DO - 10.5220/0001935001050112