ENVIRONMENT DETECTION AND ADAPTATION IN HEARING ASSISTANCE DEVICES

Abstract

Method and apparatus for environment detection and adaptation in hearing assistance devices. Performance of feature extraction and environment detection to perform adaptation to hearing assistance device operation for a number of hearing assistance environments. The system detecting various noise sources independent of speech. The system determining adaptive actions to take place based on predicted sound class. The system providing individually customizable response to inputs from different sound classes. In various embodiments, the system employing a Bayesian classifier to perform sound classifications using a priori probability data and training data for predetermined sound classes. Additional method and apparatus can be found in the specification and as provided by the attached claims and their equivalents.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a block diagram of a hearing assistance device, according to one embodiment of the present subject matter.

FIG. 2 shows a process diagram of environment detection and adaptation, according to one embodiment of the present subject matter.

FIG. 3 shows a process diagram of directionality combined with environment detection and adaptation, according to one embodiment of the present subject matter.

FIG. 4 shows a process for classification of sound sources for reception in an omnidirectional hearing assistance device, according to one embodiment of the present subject matter.

FIG. 5 shows a process for classification of sound sources for reception in a directional hearing assistance device, according to one embodiment of the present subject matter.

FIG. 6 shows a flow diagram of a detection system, according to one embodiment of the present subject matter.

FIG. 7 shows a gain diagram of a gain reduction process, according to one embodiment of the present subject matter.

FIG. 8 shows one example of environment adaptation parameters to demonstrate various controls available according to one embodiment of the present subject matter.

Claims

1. An apparatus, comprising: a microphone;an analog-to-digital (A/D) converter connected to convert analog sound signals received by the microphone into time domain digital data;a processor connected to process the time domain digital data and to produce time domain digital output, the processor including: a frequency analysis module to convert the time domain digital data into subband digital data;a feature extraction module to determine features of the subband data;an environment detection module to determine one or more sources of the subband data based on a plurality of possible sources identified by predetermined classification parameters;an environment adaptation module to provide adaptations to processing using the determination of the one or more sources of the subband data;a subband signal processing module to process the subband data using the adaptations from the environment adaptation module; anda time synthesis module to convert processed subband data into the time domain digital output.

2. The apparatus of claim 1, comprising: a digital-to-analog (D/A) converter connected to receive the time domain digital output and convert it to analog signals.

3. The apparatus of claim 2, comprising: a receiver to convert the analog signals to sound.

4. The apparatus of claim 1, wherein the environment detection module is adapted to determine sources comprising: wind, machine noise, and speech.

5. The apparatus of claim 4, wherein the speech source comprises: a first speech source associated with a user of the apparatus; and a second speech source.

6. The apparatus of claim 1, wherein the environment adaptation module includes parameter storage for each of the plurality of possible sources, the parameter storage comprising: a plurality of subband gain parameter storages.

7. The apparatus of claim 6, wherein the parameter storage further comprises: an attack parameter storage; anda release parameter storage;

8. The apparatus of claim 6, wherein the parameter storage further comprises: a misclassification threshold parameter storage.

9. The apparatus of claim 1, wherein the environment detection module comprises: a Bayesian classifier.

10. The apparatus of claim 9, wherein the environment detection module comprises storage for one or more a priori probability variables.

11. The apparatus of claim 10, wherein the environment detection module comprises storage for training data.

12. The apparatus of claim 1, further comprising: a second microphone; anda second A/D converter connected to convert analog sound signals received by the second microphone into additional time domain digital data, the additional time domain digital data combined with the time domain digital data provided to the processor for processing.

13. The apparatus of claim 1, wherein the processor further comprises a directivity module.

14. The apparatus of claim 1, wherein: the environment detection module is adapted to determine sources comprising:wind, machines, speech, a first speech source associated with a user of the apparatus, and a second speech source;the environment adaptation module includes parameter storage for each of the plurality of possible sources, the parameter storage comprising: a plurality of subband gain parameter storages, an attack parameter storage, a release parameter storage, and a misclassification threshold parameter storage; andthe environment detection module comprises a Bayesian classifier, storage for one or more a priori probability variables, and storage for training data.

15. The apparatus of claim 14, comprising: a digital-to-analog (D/A) converter connected to receive the time domain digital output and convert it to analog signals.

16. The apparatus of claim 14, comprising: a receiver to convert the analog signals to sound.

17. The apparatus of claim 14, further comprising: a second microphone; anda second A/D converter connected to convert analog sound signals received by the second microphone into additional time domain digital data, the additional time domain digital data combined with the time domain digital data provided to the processor for processing.

18. The apparatus of claim 17, wherein the processor further comprises a directivity module.

19. The apparatus of claim 18, comprising: a digital-to-analog (D/A) converter connected to receive the time domain digital output and convert it to analog signals.

20. The apparatus of claim 19, comprising: a receiver to convert the analog signals to sound.

21. A method, comprising: converting one or more time domain analog acoustic signals into frequency domain subband samples;extracting features from the subband samples using time domain analog signal information;detecting environmental parameters to categorize one or more sound sources based on a predetermined plurality of possible sound sources; andadapting processing of the subband samples using the one or more categorized sound sources.

22. The method of claim 21, wherein the detecting includes using a Bayesian classifier to categorize the one or more sound sources.

23. The method of claim 21, wherein the predetermined plurality of possible sound sources comprises: wind, machines, and speech.

24. The method of claim 23, comprising discriminating speech associated with a user of an apparatus performing the method from speech of other speakers.

25. The method of claim 21, comprising applying parameters associated with the one or more categorized sound sources, the parameters comprising: a gain adjustment, an attack parameter, a release parameter, and a misclassification threshold parameter.

26. The method of claim 25, wherein the gain adjustment is stored as individual gain settings per subband.

27. The method of claim 21, comprising adjusting directionality using detected environmental parameters.

28. The method of claim 21, comprising: processing the subband samples using hearing aid algorithms.

29. The method of claim 21, comprising: using a Bayesian classifier to categorize the one or more sound sources;discriminating speech associated with a user of an apparatus performing the method from speech of other speakers;applying parameters associated with the one or more categorized sound sources, the parameters comprising: a gain adjustment, an attack parameter, a release parameter, and a misclassification threshold parameter; andadjusting directionality using detected environmental parameters;

30. The method of claim 29, comprising: processing the subband samples using hearing aid algorithms.

31. An apparatus, comprising: a microphone;an analog-to-digital (A/D) converter connected to convert analog sound signals received by the microphone into time domain digital data;a processor connected to process the time domain digital data and to produce time domain digital output, the processor including: a frequency analysis module to convert the time domain digital data into subband digital data;feature extraction means for extracting features of the subband data;environment detection means for determining one or more sources of the subband data based on a plurality of possible sources identified by predetermined classification parameters;environment adaptation means for providing adaptations to processing using the determination of the one or more sources of the subband data; andsubband signal processing means for processing the subband data using the adaptations from the environment adaptation module.

32. The apparatus of claim 31, further comprising a second microphone and second A/D converter and directivity means for adjusting receiving microphone configuration.