Method and system for near-end detection

1. A method of soft muting suitable for use in speakerphone operations, comprising:

determining a convergence of an adaptive filter;

determining a dissimilarity between an autocorrelation of an echo estimate and an autocorrelation of a microphone signal if the adaptive filter has converged;

computing a weighting factor based on the dissimilarity;

applying the weighting factor to a voice activity level to produce a weighted voice activity level;

comparing the weighted voice activity level to a constant threshold; and

performing a muting operation on an error signal if the weighted voice activity level is less than the constant threshold, and performing a muting operation on a far-end signal if the weighted voice activity level is at least greater than the constant threshold for suppressing acoustic coupling between a loudspeaker and a microphone and allowing near end to break in.

2. The method of claim 1 , further comprising:

evaluating a change of at least one adaptive filter coefficient to determine whether the adaptive filter has converged.

3. The method of claim 1 , further comprising:

establishing the constant threshold based on the weighting factor, an energy level, and a voicing mode.

4. The method of claim 1 , further comprising

evaluating a voice activity level of the error signal, and if the voice activity level is below a threshold, not applying the weighting factor to the voice activity level for retaining a voice activity detection performance when the adaptive filter has not converged without the weighting factor.

5. A method for near-end detection suitable for use in speakerphone operations, comprising:

estimating an echo of an acoustic output signal by means of an adaptive filter operating on a far-end signal and a microphone signal by computing a first autocorrelation of the echo estimate and a second autocorrelation of the microphone signal and determining a dissimilarity between the first autocorrelation and the second autocorrelation;

suppressing the acoustic output signal in the microphone signal in view of the echo for producing an error signal;

determining a filter state of the adaptive filter;

computing a weighting factor in view of the filter state based on the dissimilarity;

estimating a voice activity level in the error signal;

applying the weighting factor to the voice activity level to produce a weighted voice activity level; and

performing a muting operation on the error signal if the weighted voice activity level is less than a constant threshold, and performing a muting operation on the far-end signal if the weighted voice activity level is at least greater than the constant threshold for suppressing acoustic coupling between the loudspeaker and the microphone and allowing the near end break in.

6. The method of claim 5 , wherein the determining a filter state further comprises:

evaluating a change of at least one adaptive filter coefficient to determine whether the adaptive filter has converged.

7. The method of claim 5 , wherein the computing a weighting further comprises:

generating the weighting factor based on the dissimilarity, wherein the dissimilarity indicates a presence of the near-end acoustic signal in the error signal.

8. The method of claim 7 , wherein the estimating a voice activity level further comprises:

computing an energy level and a voicing mode of the error signal, and the applying the weighting factor further comprises:

multiplying the energy level and the voicing mode by the weighting factor for producing the weighted voice activity level.

9. The method of claim 7 , further comprising:

estimating a first time-envelope of the first autocorrelation;

estimating a second time-envelope of the second autocorrelation; and

calculating a distortion between the first time-envelope and the second time-envelope.

10. The method of claim 9 , further comprising:

applying a low-pass filter for smoothing out the first time-envelope and the second time envelope.

11. The method of claim 9 , wherein calculating a distortion further comprises:

performing a weighted addition on a plurality of sub-frame distortions for producing the weighting factor.

12. The method of claim 11 , further comprising:

calculating a correction factor for producing the weighting factor if the weighted addition is greater than a threshold.

13. The method of claim 12 , wherein the calculating a correction factor comprises:

determining a first maximum of a sub-frame distortion;

determining a second maximum of a sub-frame distortion;

comparing the second maximum to a scaled first maximum; and

assigning at least one correction factor based on the comparing.

14. The method of claim 13 , further comprising:

multiplying the at least one correction factor to an average of the first maximum and the second maximum for producing the weighting factor.

15. A system for near-end detection suitable for use in speakerphone operations, comprising:

a loudspeaker for playing a far-end signal to produce an acoustic output signal;

a microphone for capturing the acoustic output signal and a near-end acoustic signal to produce a microphone signal;

an echo suppressor for estimating an echo of the acoustic output signal to produce an echo estimate and producing an error signal by means of an adaptive filter operating on the far-end signal and the microphone signal for suppressing acoustic coupling between the loudspeaker and the microphone;

an autocorrelation unit for computing a first autocorrelation of the echo estimate and a second autocorrelation of the microphone signal;

an envelope detector for estimating a first time-envelope of the first autocorrelation and estimating a second time-envelope of the second autocorrelation; and

a switch unit for detecting the near-end acoustic signal and performing a muting operation on the error signal if a weighted voice activity level is less than a constant threshold, and performing a muting operation on the far-end signal if a weighted voice activity level is at least greater than the constant threshold and allowing near end break in.

16. The system of claim 15 , further comprising

a voice activity detector for estimating a voice activity level in the error signal;

a weighting operator for applying a weighting factor to the voice activity level to produce the weighted voice activity level; and

a threshold unit for comparing the weighted voice activity level to a constant threshold.

17. The system of claim 15 , further comprising a processor comprising:

a low pass filter for smoothing out the first time-envelope and the second time-envelope.

18. The system of claim 17 , further comprising

a distortion unit for determining a dissimilarity between the first autocorrelation and the second autocorrelation if the adaptive filter has converged,

wherein the dissimilarity indicates a presence of the near-end acoustic signal in the error signal.

19. The system of claim 18 , wherein the distortion unit calculates a sub-frame distortion between the first time-envelope and the second time-envelope for determining the dissimilarity and generates the weighting factor based on the dissimilarity.

20. The system of claim 18 , further comprising a detector for evaluating a change of at least one adaptive filter coefficient to determine whether the adaptive filter has converged.