APPROACH TO AUTOMATIC MUSIC REMIX BASED ON STYLE TEMPLATES

    公开(公告)号:US20230360619A1

    公开(公告)日:2023-11-09

    申请号:US17737282

    申请日:2022-05-05

    Applicant: Lemon Inc.

    Abstract: In examples, a method for generating a remixed audio sample is provided. The method may include receiving an audio portion, obtaining metadata from the received audio portion, and analyzing the metadata and generating a symbolic music representation based on the analyzed metadata. In some examples, a selection of a style asset is received and applied to the symbolic music representation. Accordingly, a remixed audio portion may be rendered based on the stylized symbolic representation. That is, metadata associated with a song or song portion may be analyzed to identify a tempo, key, structure, chord, and/or progressions, etc., such that a remixed version of the song can be provided with customized instrumental arrangements and styles.

    DECENTRALIZED PROCEDURAL DIGITAL ASSET CREATION IN AUGMENTED REALITY APPLICATIONS

    公开(公告)号:US20230360280A1

    公开(公告)日:2023-11-09

    申请号:US17737569

    申请日:2022-05-05

    Applicant: Lemon Inc.

    CPC classification number: G06T11/00 G06T2200/24

    Abstract: Example implementations include a method, apparatus and computer-readable medium for decentralized procedural digital asset creation, comprising receiving a first request to create a digital asset from an application executing an augmented reality effect on a computing device, wherein the first request includes an identifier associated with a user of the application. The implementations further include generating the digital asset and metadata of the digital asset, wherein the metadata includes information about characteristics of the digital asset and ownership of the digital asset by the user. Additionally, the implementations further include storing the metadata on a blockchain. Additionally, the implementations further include receiving a second request to access the digital asset from the application. Additionally, the implementations further include transmitting, to the application for rendering, the metadata stored on the blockchain in response to validating the identifier associated with the user in the second request.

    ATTRIBUTE AND RATING CO-EXTRACTION
    104.
    发明公开

    公开(公告)号:US20230342553A1

    公开(公告)日:2023-10-26

    申请号:US17727015

    申请日:2022-04-22

    Applicant: LEMON INC.

    CPC classification number: G06F40/30 G06F40/279 G06N3/0454

    Abstract: Embodiments of the present disclosure relate to attribute and rating co-extraction. According to embodiments of the present disclosure, a method is proposed. The method comprises: determining, by a first sub-network of a model, a first feature representation based on a first token contained in a text, the first feature representation indicating semantic information of the first token in the text; determining, by a second sub-network of the model, first attribute information associated with the first token based on the first feature representation, the first attribute information indicating a first attribute involved in the text; and determining, by a third sub-network of the model, first rating information associated with the first token based on the first feature representation, the first rating information indicating a rating related to the first attribute.

    MODEL TRAINING BASED ON SYNTHETIC DATA
    106.
    发明公开

    公开(公告)号:US20230334834A1

    公开(公告)日:2023-10-19

    申请号:US18338056

    申请日:2023-06-20

    CPC classification number: G06V10/774 G06V10/764 G06T11/60

    Abstract: Embodiments of the present disclosure relate to model training based on synthetic data. According to example embodiments of the present disclosure, synthetic images are generated by providing respective text prompts into a text-to-image generation model. Respective training labels associated with the synthetic images are also generated based on the used text prompts. A target model, which is configured to perform an image classification task, is trained based at least in part on the synthetic images and the associated training labels. Through this solution, a large scale of synthetic images can be automatically obtained and applicable for training a model for image classification, to improve the model performance with data-scare setting or in the case of model pre-training where the training data amount matters.

    Power supply voltage detector, power supply voltage detection apparatus, system and medium

    公开(公告)号:US11761996B2

    公开(公告)日:2023-09-19

    申请号:US17732824

    申请日:2022-04-29

    Applicant: Lemon Inc.

    CPC classification number: G01R19/2513 G05F1/10 H03K3/037

    Abstract: The application provides an apparatus, a system, a detector and a detection method for power supply voltage detection. The apparatus connected to an integrated circuit power supply network comprises: a power supply voltage detector, comprising: N buffers, wherein an input terminal of a first buffer is connected to a clock signal, and output terminals of other buffers are connected to the input terminal of an adjacent buffer; N latch chains, each of which comprises M latches, wherein a clock input terminal of each latch is connected to a clock signal, a D terminal of a first latch of each latch chain is connected to the output terminal of a corresponding buffer, and Q terminals of other latches are connected to the D terminal of an adjacent latch, wherein M and N are positive integers, the VDD terminal of each latch is connected to an area in an integrated circuit power supply network where a power supply voltage is to be detected, and a grounding terminal of each latch is connected to a ground; and a voltage regulation module connected to the Q terminal of each latch and configured to detect data output of each latch to determine a magnitude of a power supply voltage.

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