Samsung Electronics Co., Ltd.

Saeyoung Kim

Junghwan Lee

Taehee Lee

Junghoe Kim

Sungwon Kim

Boseok Moon

Soonhyuk Hong

Hyeontaek Lim

Daehun Kim

Yongkook Kim

Yoojeong Lee

An electronic device is disclosed. The electronic device may comprise a first image sensor, a second image sensor, and a processor, wherein the processor may: acquire a first depth image and a confidence map by using the first image sensor; acquire an RGB image by using the second image sensor; acquire a second depth image on the basis of the confidence map and the RGB image; and acquire a third depth image by composing the first depth image and the second depth image on the basis of the pixel value of the confidence map.

Electronic device and method for controlling same

A robot transmits a command to control an external device around the robot based on pre-stored environment information while the robot is operating in a learning mode. The external device makes a noise as part of its operation. Also, the robot outputs user speech for learning while the external device is operating. The robot learns a speech recognition model based on the noise and speech of a user acquired through a microphone of the robot. The speech recognition model is then used by the robot or by another device to better understand the user when the user talks. The robot is then able to more accurately understand and properly execute speech commands from the user.

Robot for acquiring learning data and method for controlling thereof

A method of controlling a robot includes obtaining a first image and a second image of a plurality of objects, the first and second image being captured from different positions; obtaining, from the first and second images, a plurality of candidate positions corresponding to each of the plurality of objects, based on a capturing position of each of the first and second images and a direction to each of the plurality of objects from each capturing position; obtaining distance information between each capturing position and each of the plurality of objects in the first and second images by analyzing the first and second images; and identifying a position of each of the plurality of objects from among the plurality of candidate positions based on the distance information.

Robot and control method thereof

The present disclosure relates to an artificial intelligence (AI) system utilizing a machine learning algorithm such as deep learning, etc. and an application thereof. In particular, a controlling method of an electronic apparatus includes obtaining a user voice of a first user, converting the voice of the first user into a first spectrogram, obtaining a second spectrogram by inputting the first spectrogram to a trained model through an artificial intelligence algorithm, converting the second spectrogram into a voice of a second user, and outputting the converted second user voice. Here, the trained model is a model trained to obtain a spectrogram of a style of the second user voice by inputting a spectrogram of a style of the first user voice. In particular, at least part of the controlling method of the electronic apparatus uses an artificial intelligence model trained according to at least one of machine learning, a neural network or a deep learning algorithm.

Electronic device for modulating user voice using artificial intelligence model and control method thereof

Growing community of inventors

Suwon-si, South Korea

Saeyoung Kim