公开(公告)号：US20240420720A1

公开(公告)日：2024-12-19

申请号：US18815570

申请日：2024-08-26

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  G06N3/08 ,  G06N20/10 ,  G10L21/0208 ,  H04R3/04

Abstract: A system for performing echo cancellation includes: a processor configured to: receive a far-end signal; record a microphone signal including: a near-end signal; and an echo signal corresponding to the far-end signal; extract far-end features from the far-end signal; extract microphone features from the microphone signal; compute estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including a recurrent neural network including: an encoder including a plurality of gated recurrent units; and a decoder including a plurality of gated recurrent units; compute an estimated near-end signal from the estimated near-end features; and transmit the estimated near-end signal to the far-end device. The recurrent neural network may include a contextual attention module; and the recurrent neural network may take, as input, a plurality of error features computed based on the far-end features, the microphone features, and acoustic path parameters.

公开(公告)号：US12073847B2

公开(公告)日：2024-08-27

申请号：US17827424

申请日：2022-05-27

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  G06N3/08 ,  G06N20/10 ,  G10L21/0208 ,  H04R3/04

CPC classification number: G10L21/0232 ,  G06N3/08 ,  G06N20/10 ,  H04R3/04 ,  G10L2021/02082

Abstract: A system for performing echo cancellation includes: a processor configured to: receive a far-end signal; record a microphone signal including: a near-end signal; and an echo signal corresponding to the far-end signal; extract far-end features from the far-end signal; extract microphone features from the microphone signal; compute estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including a recurrent neural network including: an encoder including a plurality of gated recurrent units; and a decoder including a plurality of gated recurrent units; compute an estimated near-end signal from the estimated near-end features; and transmit the estimated near-end signal to the far-end device. The recurrent neural network may include a contextual attention module; and the recurrent neural network may take, as input, a plurality of error features computed based on the far-end features, the microphone features, and acoustic path parameters.

公开(公告)号：US20200312346A1

公开(公告)日：2020-10-01

申请号：US16751094

申请日：2020-01-23

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  G06N3/08 ,  H04R3/04 ,  G06N20/10

Abstract: A system for performing echo cancellation includes: a processor configured to: receive a far-end signal; record a microphone signal including: a near-end signal; and an echo signal corresponding to the far-end signal; extract far-end features from the far-end signal; extract microphone features from the microphone signal; compute estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including a recurrent neural network including: an encoder including a plurality of gated recurrent units; and a decoder including a plurality of gated recurrent units; compute an estimated near-end signal from the estimated near-end features; and transmit the estimated near-end signal to the far-end device. The recurrent neural network may include a contextual attention module; and the recurrent neural network may take, as input, a plurality of error features computed based on the far-end features, the microphone features, and acoustic path parameters.

公开(公告)号：US10803881B1

公开(公告)日：2020-10-13

申请号：US16573573

申请日：2019-09-17

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  H04R3/04 ,  G06N20/10 ,  G06N3/08 ,  G10L21/0208

Abstract: A method for performing echo cancellation includes: receiving a far-end signal from a far-end device at a near-end device; recording a microphone signal at the near-end device including: a near-end signal; and an echo signal corresponding to the far-end signal; extracting far-end features from the far-end signal; extracting microphone features from the microphone signal; computing estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including: an echo estimator including a first stack of a recurrent neural network configured to compute estimated echo features based on the far-end features; and a near-end estimator including a second stack of the recurrent neural network configured to compute the estimated near-end features based on an output of the first stack and the microphone signal; computing an estimated near-end signal from the estimated near-end features; and transmitting the estimated near-end signal to the far-end device.

公开(公告)号：US20200312345A1

公开(公告)日：2020-10-01

申请号：US16573573

申请日：2019-09-17

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  H04R3/04 ,  G06N3/08 ,  G06N20/10

Abstract: A method for performing echo cancellation includes: receiving a far-end signal from a far-end device at a near-end device; recording a microphone signal at the near-end device including: a near-end signal; and an echo signal corresponding to the far-end signal; extracting far-end features from the far-end signal; extracting microphone features from the microphone signal; computing estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including: an echo estimator including a first stack of a recurrent neural network configured to compute estimated echo features based on the far-end features; and a near-end estimator including a second stack of the recurrent neural network configured to compute the estimated near-end features based on an output of the first stack and the microphone signal; computing an estimated near-end signal from the estimated near-end features; and transmitting the estimated near-end signal to the far-end device.

公开(公告)号：US12033652B2

公开(公告)日：2024-07-09

申请号：US17827424

申请日：2022-05-27

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  G06N3/08 ,  G06N20/10 ,  G10L21/0208 ,  H04R3/04

CPC classification number: G10L21/0232 ,  G06N3/08 ,  G06N20/10 ,  H04R3/04 ,  G10L2021/02082

Abstract: A system for performing echo cancellation includes: a processor configured to: receive a far-end signal; record a microphone signal including: a near-end signal; and an echo signal corresponding to the far-end signal; extract far-end features from the far-end signal; extract microphone features from the microphone signal; compute estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including a recurrent neural network including: an encoder including a plurality of gated recurrent units; and a decoder including a plurality of gated recurrent units; compute an estimated near-end signal from the estimated near-end features; and transmit the estimated near-end signal to the far-end device. The recurrent neural network may include a contextual attention module; and the recurrent neural network may take, as input, a plurality of error features computed based on the far-end features, the microphone features, and acoustic path parameters.

公开(公告)号：US11521634B2

公开(公告)日：2022-12-06

申请号：US17015931

申请日：2020-09-09

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  H04R3/04 ,  G06N20/10 ,  G06N3/08 ,  G10L21/0208

Abstract: A method for performing echo cancellation includes: receiving a far-end signal from a far-end device at a near-end device; recording a microphone signal at the near-end device including: a near-end signal; and an echo signal corresponding to the far-end signal; extracting far-end features from the far-end signal; extracting microphone features from the microphone signal; computing estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including: an echo estimator including a first stack of a recurrent neural network configured to compute estimated echo features based on the far-end features; and a near-end estimator including a second stack of the recurrent neural network configured to compute the estimated near-end features based on an output of the first stack and the microphone signal; computing an estimated near-end signal from the estimated near-end features; and transmitting the estimated near-end signal to the far-end device.

公开(公告)号：US20220293120A1

公开(公告)日：2022-09-15

申请号：US17827424

申请日：2022-05-27

Applicant: Samsung Electronics Co., Ltd.

Inventor： Amin Fazeli ,  Mostafa El-Khamy ,  Jungwon Lee

IPC: G10L21/0232 ,  G06N3/08 ,  G06N20/10 ,  H04R3/04

Abstract: A system for performing echo cancellation includes: a processor configured to: receive a far-end signal; record a microphone signal including: a near-end signal; and an echo signal corresponding to the far-end signal; extract far-end features from the far-end signal; extract microphone features from the microphone signal; compute estimated near-end features by supplying the microphone features and the far-end features to an acoustic echo cancellation module including a recurrent neural network including: an encoder including a plurality of gated recurrent units; and a decoder including a plurality of gated recurrent units; compute an estimated near-end signal from the estimated near-end features; and transmit the estimated near-end signal to the far-end device. The recurrent neural network may include a contextual attention module; and the recurrent neural network may take, as input, a plurality of error features computed based on the far-end features, the microphone features, and acoustic path parameters.