公开(公告)号：US20230338852A1

公开(公告)日：2023-10-26

申请号：US18215531

申请日：2023-06-28

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sujung BAE ,  Kyuwon KIM ,  Jongkyu KIM ,  Tushar Balasaheb SANDHAN ,  Myoungho LEE ,  Heekuk LEE ,  Inho CHOI

IPC: A63F13/56 ,  A63F13/52 ,  G06T7/20 ,  G06F3/14

CPC classification number: A63F13/56 ,  A63F13/52 ,  G06F3/14 ,  G06T7/20

Abstract: An electronic device includes an input device, a display, a communication circuit, and a processor operatively connected to the input device, the display, and the communication circuit. The processor is configured to receive a first image frame from an external electronic device through the communication circuit; display the received first image frame, receive a first user input through the input device in a state in which the first image frame is displayed, predict a second user input on the basis of the first image frame and the first user input, generate a prediction input event corresponding to the predicted second user input, transmit information on the prediction input event to the external electronic device through the communication circuit, receive a second image frame according to the prediction input event from the external electronic device through the communication circuit and display the received second image frame.

公开(公告)号：US20210043220A1

公开(公告)日：2021-02-11

申请号：US16987475

申请日：2020-08-07

Applicant: Samsung Electronics Co., Ltd.

Inventor： Soonho BAEK ,  Kiho CHO ,  Jongmo KEUM ,  Beakkwon SON ,  Myoungho LEE ,  Yonghoon LEE ,  Hangil MOON ,  Jaemo YANG ,  Gunwoo LEE

IPC: G10L21/0232 ,  H04R1/40 ,  H04R3/00 ,  H04R29/00 ,  G10L25/51 ,  G10L25/30 ,  G10L21/0364 ,  H04S3/00 ,  G06N3/04 ,  G06N3/08

Abstract: According to an embodiment, an electronic device may include a memory configured to store a noise removal neural network model and data utilized in the noise removal neural network model and a processor electrically connected to the memory wherein the memory may store instructions that, when executed, enable the processor to: output a first channel signal using a first beamformer for a multi-channel audio signal; output a second channel signal using a second beamformer; generate a third channel signal that compensates for a difference in noise levels between the first channel signal and the second channel signal; and train the noise removal neural network model by using the third channel signal in which the difference in noise levels is compensated for and the first channel signal as input values.