Microphone array with time-frequency source discrimination

• US 20030229495A1
• Filed: 06/09/2003
• Published: 12/11/2003
• Est. Priority Date: 06/11/2002
• Status: Abandoned Application

• Current Assignee: Sony Corporation (Sony Group Corp.), Sony Electronics Inc. (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.), Sony Electronics Inc. (Sony Group Corp.)
• Inventors: Almstrand, Lars C., Konopka, Courtney
• Application Number:
  US10/457,153
• Publication Number:
  US 20030229495A1
• Time in Patent Office: Days
• US Class Current: 704/255
• CPC Class Codes: G10L 15/20 Speech recognition techniques specially adapted for robustness in adverse environments, e.g. in noise, of stress induced speech G10L21/02 takes precedence
• CPC Class Codes: G10L 2021/02166 Microphone arrays; Beamforming
• CPC Class Codes: G10L 21/0272 Voice signal separating

Abstract

A 3D microphone array is provided for, e.g., sending sound to a speech recognition (SR) engine. To increase SNR while minimizing the computational load on the SR engine, the array processor compares received time-frequency profiles from various sources of sound to a model hypothesis provided by the SR engine, and sends on to the SR engine only those profiles that are similar to the model hypothesis. If desired, sources of sound can also be discriminated against on the basis of energy level and spatial location within a room.

Claims

1. A microphone array system, comprising:

plural microphones; and

at least one array processor receiving signals from the microphones, the array processor executing logic including;

receiving at least one model time-frequency acoustic hypothesis; and

based at least in part on the model time-frequency acoustic hypothesis, selectively outputting signals representing at least one acoustic source to at least one client component.

2. The system of claim 1, wherein the client component includes at least one speech recognition engine, and the system further comprises the engine.

3. The system of claim 1, comprising at least four microphones establishing a three dimensional array.

4. The system of claim 1, wherein the logic executed by the array processor further includes selectively outputting signals to the client component based at least in part on at least one acoustic energy level received from at least one acoustic source.

5. The system of claim 1, wherein the logic executed by the array processor further includes selectively outputting signals to the client component based at least in part on at least one spatial location of at least one acoustic source.

6. The system of claim 1, further comprising at least one buffer storing signals while the array processor executes the logic, data in the buffer being selectively sent to the client component.

7. The system of claim 2, further comprising at least one feature extraction component receiving signals from the array processor and sending signals to the speech recognition engine.

8. The system of claim 7, wherein the model time-frequency acoustic hypothesis is generated by sending at least one signal from the speech recognition engine to the feature extraction component and generating a time-frequency representation of the hypothesis at the feature extraction component, prior to providing the hypothesis to the array processor.

9. The system of claim 8, wherein the hypothesis represents at least one acoustic temporal pattern.

10. The system of claim 1, wherein the hypothesis represents at least one acoustic temporal pattern.

11. The system of claim 1, further comprising the client component, wherein the client component includes at least one audio speaker.

12. A method for alleviating processing load on a speech recognition system by screening signals from acoustic sources in a space, comprising:

comparing at least one signal from at least one acoustic source in the space to at least one acoustic model; and

based at least in part on the comparing act, selectively sending the signal to the speech recognition system.

13. The method of claim 12, wherein the acoustic model is at least one time-frequency hypothesis.

14. The method of claim 12, wherein the acoustic model is at least one acoustic energy level.

15. The method of claim 12, wherein the space is predefined, and the acoustic model is at least whether a source is located in the space.

16. The method of claim 12, comprising receiving signals from acoustic sources at a multidimensional microphone array and undertaking the comparing and sending acts at the array.

17. The method of claim 16, wherein the array is a three dimensional array.

18. The method of claim 13, wherein the time-frequency hypothesis is received by the array from the speech recognition system.

19. A device embodying means for processing acoustic signals received from at least one source in at least one volume, comprising:

means for comparing signals from sources in the volume to at least one time-frequency hypothesis; and

means, responsive to the means for comparing, for sending signals to the speech recognition system.

20. The device of claim 19, further comprising:

means for defining the volume; and

means for invoking the comparing means only in response to acoustic signals received from sources within the volume.

21. The device of claim 19, further comprising:

means for invoking the comparing means only in response to acoustic signals having at least a predetermined energy.

22. The device of claim 19, further comprising the speech recognition system.

23. The device of claim 22, wherein the speech recognition system comprises means for defining the time-frequency hypothesis.

24. The device of claim 19, wherein the means for comparing is executed by a three dimensional microphone array processor.

25. The device of claim 19, wherein the means for comparing and sending are embodied in software.

26. The device of claim 19, wherein the means for comparing and sending are embodied in hardware.