Smoothing method for suppressing fluctuating artifacts during noise reduction

• US 8,892,431 B2
• Filed: 06/25/2008
• Issued: 11/18/2014
• Est. Priority Date: 06/27/2007
• Status: Expired due to Fees

• Current Assignee: Ruhr-Universitaet Bochum, Sivantos Gmbh (WS Audiology A/S)
• Original Assignee: Ruhr-Universitaet Bochum, Siemens Audiologische Technik GmbH (Siemens AG)
• Inventors: Gerkmann, Timo, Breithaupt, Colin, Martin, Rainer
• Primary Examiner(s): Opsasnick, Michael N
• Application Number:
  US12/665,526
• Publication Number:
  US 20100182510A1
• Time in Patent Office: 2,337 Days
• Field of Search: 704/226
• US Class Current: 704/226
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 25/24 the extracted parameters being the cepstrum
• CPC Class Codes: G10L 25/27 characterised by the analysis technique

Abstract

A smoothing method for suppressing fluctuating artifacts in the reduction of interference noise includes the following steps: providing short-term spectra for a sequence of signal frames, transforming each short-term spectrum by way of a forward transformation which describes the short-term spectrum using transformation coefficients that represent the short-term spectrum subdivided into its coarse and fine structures; smoothing the transformation coefficients with the respective same coefficient indices by combining at least two successive transformed short-term spectra; and transforming the smoothed transformation coefficients into smoothed short-term spectra by way of a backward transformation.

Claims

1. A smoothing method for suppressing fluctuating artifacts during noise reduction, which comprises the following steps:

providing short-term spectra for a series of signal frames, wherein a first forward transformation, using a signal from the time domain as input, generates the short-term spectra;

transforming each short-term spectrum of the short-term spectra by a second forward transformation, the second forward transformation describing the short-term spectrum using transformation coefficients which describe the short-term spectrum divided into coarse structures and fine structures thereof;

smoothing the transformation coefficients with the same coefficient indices in each case by combining at least two successive transformed short-term spectra, wherein different time constants are used for smoothing the respective transformation coefficients, wherein the time constants are chosen such that transformation coefficients describing spectral structures of fluctuating spectral magnitudes and of artifacts of noise reduction algorithms are smoothed to a greater extent than transformation coefficients typically describing spectral structures of speech; and

transforming the smoothed transformation coefficients into smoothed short-term spectra by backward transformation.

2. The smoothing method according to claim 1, which comprises using an inverse of the forward transformation for the backward transformation.

3. The smoothing method according to claim 1, which comprises using a transformation with an orthogonal base.

4. The smoothing method according to claim 1, which comprises using a transformation with a nonorthogonal base.

5. The smoothing method according to claim 1, which comprises using a discrete Fourier transform and an inverse thereof as the transformations.

6. The smoothing method according to claim 1, which comprises using fast Fourier transform and an inverse thereof as the transformations.

7. The smoothing method according to claim 1, which comprises using discrete cosine transformation and an inverse thereof for the transformations.

8. The smoothing method according to claim 1, which comprises using a discrete sine transformation and an inverse thereof for the transformations.

9. The smoothing method according to claim 1, which comprises mapping the short-term spectra nonlinearly before the forward transformation.

10. The smoothing method according to claim 9, which comprises mapping the smoothed short-term spectra nonlinearly after the backward transformation, wherein the nonlinear mapping of the backward transformation is a reversal of the nonlinear mapping of the forward transformation.

11. The smoothing method according to claim 9, which comprises mapping the short-term spectra nonlinearly before the forward transformation by logarithmization.

12. The smoothing method according to claim 1, which comprises using recursive smoothing for smoothing the transformation coefficients.

13. The smoothing method according to claim 1, which comprises using nonrecursive smoothing for smoothing the transformation coefficients.

14. The smoothing method according to claim 1, which comprises applying smoothing to an absolute value or to a power of the absolute value of the short-term spectra.

15. The smoothing method according to claim 1, wherein the short-term spectrum is a spectral weighting function of a noise reduction algorithm.

16. The smoothing method according to claim 1, wherein the short-term spectrum is a spectral weighting function of a post filter for multichannel methods for noise reduction.

17. The smoothing method according to claim 15, wherein the spectral weighting function results from a minimization of an error criterion.

18. The smoothing method according to claim 1, wherein the short-term spectrum is a filtered short-term spectrum.

19. The smoothing method according to claim 1, wherein the short-term spectrum is a spectral weighting function of a multichannel method for noise reduction.

20. The smoothing method according to claim 1, wherein the short-term spectrum is an estimated coherence or an estimated “

magnitude squared coherence”

between at least two microphone channels.

21. The smoothing method according to claim 1, wherein the short-term spectrum is a spectral weighting function of a multichannel method for speaker or source separation.

22. The smoothing method according to claim 1, wherein the short-term spectrum is a spectral weighting function of a multichannel method for speaker separation on a basis of phase differences for signals in different channels.

23. The smoothing method according to claim 1, wherein the short-term spectrum is a spectral weighting function of a multichannel method for noise reduction on a basis of a “

generalized cross-correlation.”

24. The smoothing method according to claim 1, wherein the short-term spectrum contains spectral magnitudes containing both voice and noise components.

25. The smoothing method according to claim 1, wherein the short-term spectrum is an estimate of a signal-to-noise ratio.

26. The smoothing method according to claim 1, wherein the short-term spectrum is an estimate of a noise power.

27. The smoothing method according to claim 1, wherein the short-term spectrum comprises transformed signal frames of an image signal, and the coefficients of the transformed image signal calculated row by row or column by column or two-dimensionally are subjected to spatial smoothing with different smoothing parameters.

28. The smoothing method according to claim 27, wherein the image signal is a video signal.

29. The smoothing method according to claim 1, which comprises using, as the short-term spectrum, a transformed medical signal derived from the human body.

30. The smoothing method according to claim 1, which comprises using the smoothing method in a post filter, in combination with a post filter, as part of an error masking method, or in connection with a method for voice and/or image coding.

31. The smoothing method according to claim 1, which comprises using the smoothing method at a receiver end.

32. The smoothing method according to claim 1, which comprises using the smoothing method in a telecommunication network and/or during a broadcast transmission for improving a voice and/or image quality and for suppressing artifacts.