PRIVACY PROTECTION IN COLLECTIVE FEEDFORWARD

• US 20170269901A1
• Filed: 06/08/2017
• Published: 09/21/2017
• Est. Priority Date: 11/25/2015
• Status: Active Grant

• Current Assignee: Dolby Laboratories Licensing Corporation (Dolby Laboratories Incorporated)
• Original Assignee: Doppler Labs, Inc.
• Inventors: Klimanis, Gints, Kraft, Noah, Jaffe, Matthew J., Lanman, III, Richard Fritz, Baker, Jeff
• Granted Patent: US 10,275,210 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 3/165 Management of the audio stream, e.g. setting of volume, audio stream path
• CPC Class Codes: G10L 25/03 characterised by the type of extracted parameters
• CPC Class Codes: H04L 67/30 Profiles
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04R 1/1083 Reduction of ambient noise active noise reduction per se G10K11/175; protective devices for the ear, e.g. providing acoustic protection A61F11/06
• CPC Class Codes: H04R 2460/01 Hearing devices using active noise cancellation
• CPC Class Codes: H04R 2460/07 Use of position data from wide-area or local-area positioning systems in hearing devices, e.g. program or information selection
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/025 using location based information parameters
• CPC Class Codes: H04W 4/33 for indoor environments, e.g. buildings

Abstract

Personal audio systems and methods are disclosed. A personal audio system includes a processor to generate a personal audio stream by processing an ambient audio stream in accordance with an active processing parameter set, a circular buffer memory to store a most recent snippet of the ambient audio stream, and an event detector to detect a trigger event. In response to detection of the trigger event, a controller may extract audio feature data from the most recent snippet of the ambient audio stream and transmit the audio feature data and associated metadata to a knowledgebase remote from the personal audio system.

Claims

1. A system, comprising:

a processor configured to;

analyze audio feature data and associated metadata received from a personal audio system, wherein the audio feature data is extracted from a most recent snippet of an ambient audio stream;

develop a new processing parameter set based on the audio feature data; and

provide the new processing parameter set to personal audio system and one or more other personal audio systems; and

a memory coupled the processor and configured to store the new processing parameter set.

2. The system of claim 1, wherein the processor is further configured to receive the audio feature data in response to a trigger event associated with the personal audio system.

3. The system of claim 2, wherein the trigger event includes retrieving a selected processing parameter set from a dataset memory of the personal audio system for use as an active processing parameter set.

4. The system of claim 2, wherein

the trigger event includes receiving, via the user interface, a command to store an active processing parameter set in a dataset memory, and

the associated metadata transmitted to the device includes the active processing parameter set.

5. The system of claim 1, wherein the associated metadata includes the active processing parameter set before modification.

6. The system of claim 1, wherein the associated metadata transmitted to the device includes a descriptor received from a user via a user interface.

7. The system of claim 1, wherein the associated metadata transmitted to the device includes data indicating the location of the personal audio system.

8. The system of claim 1, wherein the audio feature data includes one or more of arithmetic mean, geometric mean, harmonic mean, centroid, variance, standard deviation, spectral skew, kurtosis, spectral shape, rolloff, spread, flatness, spectral flux, Mel frequency cepstral coefficients, pitch, tonal power ratio, harmonic-to-average power ratio, maximum of autocorrelation function, zero crossing rate, RMS power, peak power, crest factor, amplitude/power envelope and attack/decay rates.

9. The system of claim 1, wherein the processor is configured to develop the new processing parameter set using one or more machine learning techniques.

10. The system of claim 1, wherein the processor is configured to develop the new processing parameter set using one or more analytical techniques.

11. The system of claim 1, wherein to develop a new processing parameter set includes:

sorting the audio feature data and associated metadata from the personal audio system and additional audio feature data and associated metadata from the other personal audio systems into a plurality of clusters; and

developing a corresponding consensus processing parameter set for each cluster of the plurality of clusters.

12. The system of claim 11, wherein the plurality of clusters are sorted based on the associated metadata from the personal audio system and the associated metadata from the other personal audio systems.

13. The system of claim 11, wherein the corresponding consensus processor parameter set is based on a median or average of processing parameters associated with a cluster.

14. The system of claim 11, wherein an outlier processing parameter is discarded from a cluster.

15. A method, comprising:

analyzing audio feature data and associated metadata received from a personal audio system, wherein the audio feature data is extracted from a most recent snippet of an ambient audio stream;

developing a new processing parameter set based on the audio feature data; and

providing the new processing parameter set to personal audio system and one or more other personal audio systems.

16. The method of claim 15, further comprising receiving the audio feature data in response to a trigger event associated with the personal audio system.

17. The method of claim 15, wherein developing a new processing parameter set includes:

sorting the audio feature data and associated metadata from the personal audio system and additional audio feature data and associated metadata from the other personal audio systems into a plurality of clusters; and

developing a corresponding consensus processing parameter set for each cluster of the plurality of clusters.

18. The method of claim 17, wherein the plurality of clusters are sorted based on the associated metadata from the personal audio system and the associated metadata from the other personal audio systems

19. The method of claim 17, wherein the corresponding consensus processor parameter set is based on a median or average of processing parameters associated with a cluster.

20. A computer program product, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for:

analyzing audio feature data and associated metadata received from a personal audio system, wherein the audio feature data is extracted from a most recent snippet of an ambient audio stream;

developing a new processing parameter set based on the audio feature data; and

providing the new processing parameter set to personal audio system and one or more other personal audio systems.