VOICE CONVERSATION ANALYSIS METHOD AND APPARATUS USING ARTIFICIAL INTELLIGENCE

    公开(公告)号:US20210012766A1

    公开(公告)日:2021-01-14

    申请号:US17040746

    申请日:2019-03-26

    Abstract: The present invention relates to a voice conversation analysis apparatus and a method therefor and, more specifically, to: a voice conversation analysis apparatus categorizing voices generated during a voice conversation so as to predict required functions and further analyzing the voices so as to provide proper functions; and a method therefor. In addition, disclosed are: an artificial intelligence (AI) system for simulating the functions of recognition, decision-making, and the like of the human brain by using a machine learning algorithm; and an application thereof. According to one embodiment, disclosed in an electronic device control method for performing an operation through a suitable operating mode by using an AI learning model so as to analyze a voice conversation, comprising the steps of: receiving a voice and acquiring information on the voice; acquiring category information on the voice on the basis of the information on the voice so as to determine at least one operating mode corresponding to the category information; and performing an operation related to the operating mode by using an AI model corresponding to the determined operating mode.

    ELECTRONIC DEVICE AND METHOD FOR RENDERING BASED ON TRACKING INFORMATION FOR USER'S MOVEMENT

    公开(公告)号:US20240177431A1

    公开(公告)日:2024-05-30

    申请号:US18451498

    申请日:2023-08-17

    Abstract: An electronic device is provided. The electronic device may comprise at least one processor, a tracking sensor, a communication circuit, and a display. The at least one processor may obtain first tracking information for a movement of a user through the tracking sensor. The at least one processor may receive, from an external electronic device through the communication circuit, image property information to request a rendering. The at least one processor may identify a tracking property of a first image based on the image property information. The at least one processor may determine a rendering start timing for the first image having the tracking property based on a rendering processing time. The at least one processor may transmit, to the external electronic device through the communication circuit, a message including the image property information of the first image and the first tracking information, based on the rendering start timing for the first image. The at least one processor may receive, from the external electronic device through the communication circuit, a first rendering image rendered based on the image property information of the first image and the first tracking information. The at least one processor may display, through the display, a second rendering image generated based on the first rendering image. The image property information of the first image may comprise information on whether an object included in the first image is rendered based on tracking information.

    ELECTRONIC DEVICE AND CONTROL METHOD THEREOF

    公开(公告)号:US20210256965A1

    公开(公告)日:2021-08-19

    申请号:US17269947

    申请日:2019-07-26

    Abstract: An electronic device of the present disclosure comprises: a communication unit; a memory; and a processor for: detecting a voice section in an audio signal acquired by the electronic device; identifying whether a wake-up word stored in the memory exists in a user voice included in the detected voice section; when it is identified that the wake-up word exists in the user voice, transmitting, via the communication unit, the user voice to a server for providing a voice recognition service; and when response information for the user voice is received from the server, providing a response to the user voice on the basis of the received response information, wherein the processor identifies that the wake-up word exists in the user voice, when a part of the user voice matches the wake-up word. In particular, a method for acquiring a natural language for providing a response may use an artificial intelligence model learned according to at least one of machine learning, a neural network, and a deep learning algorithm.

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