Electronic apparatus and method for controlling thereof

    公开(公告)号:US12131738B2

    公开(公告)日:2024-10-29

    申请号:US17944401

    申请日:2022-09-14

    CPC classification number: G10L15/22 G10L15/02 G10L15/26 G10L2015/223

    Abstract: 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 electronic apparatus

    公开(公告)号:US11928111B2

    公开(公告)日:2024-03-12

    申请号:US17739453

    申请日:2022-05-09

    CPC classification number: G06F16/2452 G06N3/02

    Abstract: 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.

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