Methods and systems for robust beamforming

US9502021B1 · US · B1

Patent metadata
FieldValue
Publication numberUS-9502021-B1
Application numberUS-201414510838-A
CountryUS
Kind codeB1
Filing dateOct 9, 2014
Priority dateOct 9, 2014
Publication dateNov 22, 2016
Grant dateNov 22, 2016

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

Official abstract text for this publication.

Provided are methods and systems for spatially selecting acoustic sources using a post-processor that consists of a selection of one postfilter from a set of postfilters, or a cascade of postfilters, where each postfilter is optimal for a particular scenario. Each postfilter individually is based on optimizing the gain for each time-frequency bin based on knowledge of (i) a spatial covariance matrix for the desired source, (ii) a spatial covariance matrix for the interfering sources, and (iii) microphone signals in some neighborhood of the current time-frequency bin.

First claim

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The invention claimed is: 1. A system comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to for one or more coefficients characterizing an output signal: select a desired-source scenario from a set of predefined desired-source scenarios to maximize the amplitude of the output signal; select an interference scenario from a set of predefined interference scenarios to minimize the amplitude of the output signal; and apply a gain to the output signal based on the selected desired-source scenario and the selected interference scenario, wherein the output signal with the applied gain is used as the processor output signal. 2. The system of claim 1 , wherein the at least one processor is further caused to: select the desired-source scenario based on sensor input signals and quantitative predefined scenario descriptions. 3. The system of claim 1 , wherein the at least one processor is further caused to: select the interference scenario based on sensor input signals and quantitative predefined scenario descriptions. 4. The system of claim 2 , wherein the quantitative predefined scenario descriptions are covariance matrices. 5. The system of claim 3 , wherein the quantitative predefined scenario descriptions are covariance matrices. 6. The system of claim 1 , wherein the set of predefined interference scenarios include at least one interference scenario and a reflection of the at least one interference scenario around 0 degrees. 7. The system of claim 2 , wherein the set of predefined desired-source scenarios represent angles over a range spanning a desired beamwidth. 8. The system of claim 1 , wherein the at least one processor is further caused to: select the desired-source scenario based on sensor input signals and adaptable predefined scenario descriptions. 9. The system of claim 1 , wherein the at least one processor is further caused to: select the interference scenario based on sensor input signals and adaptable predefined scenario descriptions. 10. The system of claim 8 , wherein the adaptable predefined scenario descriptions are covariance matrices. 11. The system of claim 9 , wherein the adaptable predefined scenario descriptions are covariance matrices. 12. A computer-implemented method comprising: for one or more coefficients characterizing an output signal: selecting a desired-source scenario from a set of predefined desired-source scenarios; selecting an interference scenario from a set of predefined interference scenarios; and applying a gain to the output signal based on the selected desired-source scenario and the selected interference scenario, wherein the desired-source scenario is selected to maximize the amplitude of the output signal and the interference scenario is selected to minimize the amplitude of the output signal, based on sensor input signals and quantitative predefined scenario descriptions, and wherein the output signal with the applied gain is used as the processor output signal. 13. The method of claim 12 , wherein the desired-source scenario is selected to maximize the amplitude of the output signal based on sensor input signals and adaptable predefined scenario descriptions. 14. The method of claim 12 , wherein the interference scenario is selected to minimize the amplitude of the output signal based on sensor input signals and adaptable predefined scenario descriptions. 15. The method of claim 12 , wherein the quantitative predefined scenario descriptions are covariance matrices. 16. The method of claim 13 , wherein the adaptable predefined scenario descriptions are covariance matrices. 17. The method of claim 14 , wherein the adaptable predefined scenario descriptions are covariance matrices. 18. A system comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to, for one or more coefficients characterizing an output signal: combine a plurality of numbers, each number being a gain associated with a unique pair of a desired-source scenario selected from a set of predefined desired-source scenarios, and an interference scenario selected from a set of predefined interference scenarios, wherein the plurality of numbers are combined such that the resulting number approaches a largest desired-source scenario number and a smallest interference scenario number, and wherein the resulting number is used to multiply said coefficients to render new coefficients characterizing a new output signal. 19. The system of claim 18 , wherein the at least one processor is further caused to: mask interference of the desired source signal based on the combined plurality of numbers. 20. A system comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to: multiply a time-frequency coefficient that forms a component of a representation of a beamformer output signal or a single microphone output signal by a real number that minimizes the squared difference between a resulting scaled coefficient and a desired-source signal; and adjust the desired-source signal to compensate for the desired-source signal traveling from a location of the source to a location of the beamformer or the single microphone. 21. The system of claim 20 , wherein the adjustment to the desired-source signal is further based on compensating for successive processing by the beamformer. 22. The system of claim 20 , wherein the at least one processor is further caused to: limit a computed gain to be between 0 and 1. 23. The system of claim 22 , wherein the limited gain is computed using g * = 1 - min ⁡ ( α ,  R _ ψ  w  R _ ψ 

Assignees

Inventors

Classifications

  • G10K11/175Primary

    using interference effects; Masking sound · CPC title

  • G10K11/348Primary

    using amplitude variation · CPC title

  • by changing the amplitude · CPC title

  • characterised by the method used for estimating noise · CPC title

  • Microphone arrays; Beamforming · CPC title

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What does patent US9502021B1 cover?
Provided are methods and systems for spatially selecting acoustic sources using a post-processor that consists of a selection of one postfilter from a set of postfilters, or a cascade of postfilters, where each postfilter is optimal for a particular scenario. Each postfilter individually is based on optimizing the gain for each time-frequency bin based on knowledge of (i) a spatial covariance m…
Who is the assignee on this patent?
Google Inc
What technology area does this patent fall under?
Primary CPC classification G10K11/175. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Nov 22 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).