METHODS AND APPARATUS FOR IMPROVED ECHO SUPPRESSION IN COMMUNICATIONS SYSTEMS

Patent №

US 6,160,886

Granted

2000-12-12

Filed 1998

Owner

ERICSSON INC.

Lab

AI components

1

speech

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09005149

Methods and apparatus for achieving echo suppression in communications systems include an echo suppressor, referred to herein as an AC-center attenuator, which attenuates the echo component of a communications signal by multiplying a portion of the communications signal by an appropriate scale factor. Specifically, the AC-center attenuator scales that portion of the communications signal lying within a sliding attenuation window. The attenuation window tracks the communications signal so that the AC-center attenuator suppresses the echo component while passing other signal components of interest (e.g., near-end speech and noise). The scale factor within the attenuation window, and the size of the attenuation window itself, are dynamically adjusted so that the AC-center attenuator introduces minimum signal distortion and few audible artifacts. The dynamic adjustment is carried out to provide a desired round-trip echo gain in a system in which the AC-center attenuator is implemented. Toward that end, a measure of the echo attenuation achieved by an echo suppressor (e.g., an adaptive echo canceler) is obtained by computing a ratio of first and second values, wherein the first and second values indicate energy levels in the echo suppressor output and input signals, respectively. Alternately, the echo attenuation achieved by a blockwise-updating echo canceler is obtained by computing a ratio of first and second values, wherein the first value indicates a level of energy in a set of update coefficients of the echo canceler and the second value indicates a level of energy in the echo canceler input signal. In each case, the computed ratio can be used to adjust the level of attenuation provided by a residual echo suppressor.

SpeechH04M 9/08H04M 9/082

AI classification

Speech0.84
Machine learning0.03
AI hardware0.03
Knowledge representation0.03
Planning0.02
Natural language0.00
Vision0.00
Evolutionary computation0.00

Ownership

ERICSSON INC.

assignment · 91930736

Assignors

ROMESBURG, ERIC DOUGLAS, RASMUSSON, JIM AGNE JERKER

On an employer assignment, the assignors are typically the inventors.

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