US 12,406,683 B2
Kalmannet: a learnable Kalman filter for acoustic echo cancellation
Meng Yu, Palo Alto, CA (US); Hao Zhang, Palo Alto, CA (US); and Dong Yu, Palo Alto, CA (US)
Assigned to TENCENT AMERICA LLC, Palo Alto, CA (US)
Filed by TENCENT AMERICA LLC, Palo Alto, CA (US)
Filed on Jun. 1, 2023, as Appl. No. 18/327,447.
Prior Publication US 2024/0404541 A1, Dec. 5, 2024
Int. Cl. G10L 21/0216 (2013.01); G10L 21/0208 (2013.01)
CPC G10L 21/0216 (2013.01) [G10L 2021/02082 (2013.01); G10L 2021/02163 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of acoustic echo cancellation (AEC), the method performed by at least one processor and comprising:
receiving an audio signal obtained from a microphone;
inputting the audio signal into a neural-network based AEC model, wherein the neural-network based AEC model is trained using a training audio signal; and
outputting an AEC signal from the neural-network based AEC model in which AEC is applied to the audio signal, wherein the AEC signal is a version of the audio signal in which acoustic echo noise of the audio signal is suppressed and target audio of the audio signal is sustained, and wherein the neural-network based AEC model outputs the AEC signal based on estimating a far-end non-linear distortion, a transition factor, and a non-linear transition function.