Samsung Electronics Co., Ltd.

Hejung Yang

Jisang Yu

Sangwon Lee

Jaeyoung Roh

Indong Lee

Haengsun Lim

Hojun Jin

Sungsoo Kim

Kwangyoun Kim

Jonghyun Kim

Hyungjun Lim

Yoonjung Choi

Yeaseul Song

Donghan Jang

Hyojung Han

Jubum Han

An electronic apparatus is disclosed. The electronic apparatus may include a microphone; a communication interface; a memory configured to store at least one instruction; and a processor configured to execute the at least one instruction to: obtain a user voice input for registering a wake-up voice input via the microphone; input the user voice input into a trained neural network model to obtain a first feature vector corresponding to text included in the user voice input; receive a verification data set determined based on information related to the text included in the user voice input from an external server via the communication interface; input a verification voice input included in the verification data set into the trained neural network model to obtain a second feature vector corresponding to the verification voice input; and identify whether to register the user voice input as the wake-up voice input based on a similarity between the first feature vector and the second feature vector.

Electronic apparatus and method for controlling thereof

Provided is an electronic apparatus. A method of controlling the electronic apparatus includes displaying at least one sentence, when receiving a user input regarding at least one character of the at least one sentence that is displayed, analyzing the at least one sentence by using the at least one sentence including at least one character and the at least one character, selecting a character set included in the at least one sentence according to an analysis result, and displaying a selected character set to be distinguished from other characters included in the at least one sentence.

Electronic device, and method for controlling electronic device

An electronic apparatus is provided. The electronic apparatus may include a microphone; a memory configured to store a wakeup word; and a processor configured to: identify, based on context information of the electronic apparatus, an occurrence of a pre-determined event; change, based on the occurrence of the pre-determined event, a first threshold value for recognizing the wakeup word; obtain, based on a first user voice input received via the microphone, a similarity value between first text information corresponding to the first user voice input and the wakeup word; and perform, based on the similarity value being greater than or equal to the first threshold value, a voice recognition function on second text information corresponding to a second user voice input received via the microphone after the first user voice input.

Electronic apparatus and controlling method thereof

A method for controlling an electronic apparatus includes: translating a first query text of a first language to acquire a second query text of a second language; transmitting the second query text to an external device; acquiring, from the external device, a first response text of the second language in response to the second query text; acquiring a second response text acquired by translating the first response text into the first language, and identifying whether the second response text semantically matches to the first query text by inputting the second response text and the first query text into a first neural network model configured to identify whether a query and a response semantically match; and acquiring a third query text of the second language by retranslating the first query text based on a result of identifying that the first query text and the second response text do not semantically match.

Electronic apparatus and method for controlling electronic apparatus

Provided are a server, a client device, and operation methods thereof for training a language model. The server, the client device, and the operation methods thereof identify a word or phrase including a named entity that is incorrectly pronounced by a user or is difficult for the user to accurately pronounce from an input text for use in training a natural language understanding (NLU) model, generate text candidates for use in training the NLU model by replacing the identified word or phrase with a word or phrase predicted to be uttered by the user and having high phonetic similarity to the identified word or phrase, and train the NLU model by using the generated text candidates.

Server, client device, and operation methods thereof for training natural language understanding model

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Suwon-si, South Korea

Hejung Yang