Gathering user's speech samples
    14.
    发明授权

    公开(公告)号:US11521621B2

    公开(公告)日:2022-12-06

    申请号:US17028527

    申请日:2020-09-22

    Abstract: Disclosed is gathering a user's speech samples. According to an embodiment of the disclosure, a method of gathering learning samples may gather a speaker's speech data obtained while talking on a mobile terminal and text data generated from the speech data and gather training data for generating a speech synthesis model. According to the disclosure, the method of gathering learning samples may be related to artificial intelligence (AI) modules, unmanned aerial vehicles (UAVs), robots, augmented reality (AR) devices, virtual reality (VR) devices, and 5G service-related devices.

    Emotion classification information-based text-to-speech (TTS) method and apparatus

    公开(公告)号:US11514886B2

    公开(公告)日:2022-11-29

    申请号:US16485421

    申请日:2019-01-11

    Abstract: Disclosed are an emotion classification information-based text-to-speech (TTS) method and device. The emotion classification information-based TTS method according to an embodiment of the present invention may, when emotion classification information is set in a received message, transmit metadata corresponding to the set emotion classification information to a speech synthesis engine and, when no emotion classification information is set in the received message, generate new emotion classification information through semantic analysis and context analysis of sentences in the received message and transmit the metadata to the speech synthesis engine. The speech synthesis engine may perform speech synthesis by carrying emotion classification information based on the transmitted metadata.

    Speech synthesizer using artificial intelligence, method of operating speech synthesizer and computer-readable recording medium

    公开(公告)号:US11227578B2

    公开(公告)日:2022-01-18

    申请号:US16499755

    申请日:2019-05-15

    Abstract: A speech synthesizer using artificial intelligence includes a memory configured to store a first ratio of a word classified into a minor class among a plurality of classes and a synthesized speech model, and a processor configured to determine a class classification probability set of the word using the word, the first ratio and the synthesized speech model. The first ratio indicates a ratio in which the word is classified into the minor class within a plurality of characters, the plurality of classes includes a first class corresponding to first reading break, a second class corresponding to second reading break greater than the first break and a third class corresponding to third reading break greater than the second break, and the minor class has a smallest count among the first to third classes.

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