Adaptive beamformer using a log domain optimization criterion

• US 8,401,206 B2
• Filed: 01/15/2009
• Issued: 03/19/2013
• Est. Priority Date: 01/15/2009
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Seltzer, Michael Lewis, Tashev, Ivan Jelev
• Primary Examiner(s): Chin, Vivian
• Assistant Examiner(s): Zhang, Leshui
• Application Number:
  US12/353,986
• Publication Number:
  US 20100177908A1
• Time in Patent Office: 1,524 Days
• Field of Search: 381/92, 381/71.1, 381/71.11, 381/71.12, 381/94.2, 381/122, 381/94.1, 381/94.3, 381/71.6, 704/233, 704/E15.039, 704/231, 379/406.08, 379/406.12
• US Class Current: 381/92
• CPC Class Codes: H04R 1/406 microphones
• CPC Class Codes: H04R 3/005 for combining the signals of two or more microphones specially adapted for hearing aids H04R25/407

Abstract

Described is a audio signal processing technology in which an adaptive beamformer processes input signals from microphones based on an estimate received from a pre-filter. The adaptive beamformer may compute its parameters (e.g., weights) for each frame based on the estimate, via a magnitude-domain objective function or log-magnitude-domain objective function. The pre-filter may include a time invariant beamformer and/or a non-linear spatial filter, and/or may include a spectral filter. The computed parameters may be adjusted based on a constraint, which may be selectively applied only at desired times.

Claims

1. In a computing environment, a method comprising:

receiving input signals from a plurality of microphones at an adaptive beamformer and a time invariant beamformer, the adaptive beamformer including an adaptive beamformer algorithm;

receiving an output estimation from a non-linear spatial filter that is based on the input signals, wherein the non-linear spatial filter uses the input signals to compute a probability of a signal direction for each of the input signals, and wherein the non-linear spatial filter computes the output estimation using output from the time invariant beamformer and the probability computed;

computing parameters of the adaptive beamformer algorithm using the output estimation from the non-linear spatial filter and an output signal from the adaptive beamformer, wherein the output signal is used to compute weights for each of the plurality of microphones; and

processing the input signals into the output signal using the parameters of the adaptive beamformer algorithm.

2. The method of claim 1 wherein the output estimation corresponds to a particular frequency bin, and further comprising, receiving at least one other estimation corresponding to at least one other frequency bin.

3. The method of claim 1 wherein using the output estimation to compute the parameters comprises using a magnitude corresponding to the output estimation in a magnitude-domain objective function.

4. The method of claim 1 wherein using the output estimation comprises to compute the parameters comprises using a log-based magnitude computation corresponding to the output estimation in a log magnitude-domain objective function.

5. The method of claim 1 further comprising, using the non-linear spatial filter comprises using spatial information in the non-linear spatial filter to determine the output estimation.

6. The method of claim 1 further comprising, using the non-linear spatial filter comprises using spectral information in the non-linear spatial filter to determine the output estimation.

7. The method of claim 1 further comprising using a constraint to further vary the input signals from the microphones into the output signal.

8. The method of claim 1 further comprising, using a partial constraint to occasionally further vary the input signals from the microphones into the output signal.

9. The method of claim 1 further comprising smoothing the parameters based upon parameters corresponding to at least one prior frame.

10. In a computing environment, a system comprising:

at least one processor;

a memory communicatively coupled to the at least one processor;

an output estimation mechanism implemented on the at least one processor and configured to receive input signals from a plurality of microphones and configured to generate an output estimation including magnitude information, wherein the input signals are used to compute a probability of a signal direction for each of the input signals, and wherein the output estimation mechanism generates the output estimation using output from a time invariant beamformer and the probability computed, wherein the time invariant beamformer generates the output using the input signals; and

an adaptive beamformer having an adaptive beamformer algorithm, the adaptive beamformer configured to receive the output estimation and the input signals, the adaptive beamformer algorithm configured to combine the input signals using weights dependent on the output estimation to generate an output signal, wherein the weights are computed for each of the plurality of microphones using the output estimation, and wherein the output signal is based on the weights computed and the input signals.

11. The system of claim 10 wherein the adaptive beamformer computes the weights via a magnitude-domain objective function.

12. The system of claim 10 wherein the adaptive beamformer computes the weights via a log-magnitude-domain objective function.

13. The system of claim 10 wherein the adaptive beamformer computes the weights via a log-power-domain objective function.

14. The system of claim 10 wherein the estimation mechanism comprises a time invariant beamformer coupled to a non-linear spatial filter.

15. The system of claim 10 wherein the estimation mechanism includes a pre-filter that processes spectral information.

16. The system of claim 10 further comprising a constraint mechanism that when operative, constrains at least one of the weights.

17. One or more tangible computer-readable storage devices having computer-executable instructions stored thereon, which in response to execution by a computer, cause the computer to perform steps comprising:

receiving input signals from a plurality of microphones at a time invariant beamformer, a non-linear spatial filter, and an adaptive beamformer;

using the input signals to compute a probability of a signal direction for each of the input signals at the non-linear spatial filter;

receiving an output from the time invariant beamformer at the non-linear spatial filter;

using the output from the time invariant beamformer and the probability of the signal direction for each of the input signals to compute an output estimation at the non-linear spatial filter;

receiving the output estimation from the non-linear spatial filter at the adaptive beamformer;

using the output estimation and a combined signal from the adaptive beamformer to compute weights for each of the plurality of microphones; and

outputting the combined signal from the adaptive beamformer that is based on the weights for each of the plurality of microphones and the input signals.

18. The one or more tangible computer-readable storage devices of claim 17 wherein using the output estimation received from the time invariant beamformer at the adaptive beamformer comprises using a log-based magnitude computation.

19. The one or more tangible computer-readable storage devices of claim 17 having further computer-executable instructions stored thereon, which in response to execution by the computer, cause the computer to perform steps further comprising, using a constraint to adjust the parameters.

20. The one or more tangible computer-readable storage devices of claim 19 having further computer-executable instructions stored thereon, which in response to execution by the computer, cause the computer to perform steps further comprising, selectively deciding when to use the constraint and when not to use the constraint.