US 12,700,418 B1Granted

Per frame input estimation for post filter echo suppression

AssigneeAmazon Technologies, Inc.

InventorsKarim Helwani, Michael Mark Goodwin, Erfan Soltanmohammadi

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Abstract

Per frame inputs for post filter echo suppression are determined. Captured audio data of a two-way communication that includes a far-end signal played via a speaker may be processed as different sub-bands of individual frames. A machine learning model may be applied that is trained to accept the different sub-bands of a frame and corresponding sub-bands of a corresponding frame of the far-end audio data as inputs to generate outputs that can be used as post-filter inputs for the frame. The post-filter inputs that are output from the machine learning model may include an attenuation parameter, near-end estimate and echo estimate. A post filter may be applied to the different sub-bands of the frame sing the post-filter inputs to remove echo data caused by the far-end audio data in the captured audio data.

Claims20

Dependent claims

A system, comprising:

a microphone;
a speaker
at least one processor;
and
a memory, storing program instructions that when executed by the at least one processor, cause the at least one processor to:
receive captured audio data of a two-way communication via the microphone in a location that includes the speaker that plays far-end audio data of the two-way communication;
generate enhanced audio data from the captured audio data to suppress echo caused by inclusion of the far-end audio data in the captured audio data, wherein to generate the enhanced audio data, the program instructions cause the at least one processor to:
respectively process individual frames of the captured audio data in a sub-band domain as a plurality of different sub-bands, wherein to respectively process the individual frames, the program instructions cause the at least one processor to:
apply a machine learning model, trained to:
accept, as inputs, the plurality of different sub-bands of a frame of the captured audio data and corresponding sub-bands of a corresponding frame of the far-end audio data;
and
generate, as outputs, post-filter inputs for the frame of the captured audio data, wherein the post filter inputs comprise an attenuation parameter, a near-end estimate, and echo estimate;
apply a post-filter to the plurality of different sub-bands of the frame of the captured audio data according to the attenuation parameter and a ratio of the near-end estimate to the echo estimate to generate an enhanced frame to include as part of the enhanced audio data;
and
send the enhanced audio data to a destination.

12 more elements

One or more non-transitory, computer-readable storage media, storing program instructions that when executed on or across one or more computing devices cause the one or more computing devices to implement:

receiving captured audio data of a two-way communication via a microphone in a location that includes a speaker that plays far-end audio data of the two-way communication;
for individual frames of the captured audio data that are respectively processed as a plurality of different sub-bands:
applying a machine learning model, trained to:
accept, as inputs, the plurality of different sub-bands of a frame of the captured audio data and corresponding sub-bands of a corresponding frame of the far-end audio data;
and
generate, as outputs, post-filter inputs for the frame of the captured audio data, wherein the post filter inputs comprise an attenuation parameter, a near-end estimate, and echo estimate;
applying a post-filter to the plurality of different sub-bands of the frame of the captured audio data according to the attenuation parameter and a ratio of the near-end estimate to the echo estimate remove echo data caused by the far-end audio data in the captured audio data to generate an enhanced frame of the captured audio data;
and
sending the generated enhanced frames of the captured audio data to a destination.

6 more elements

Dependencies are inferred from the claim text.