SOUND PROCESSING METHOD, SOUND PROCESSING APPARATUS, AND RECORDING MEDIUM

    公开(公告)号:US20210005176A1

    公开(公告)日:2021-01-07

    申请号:US17027058

    申请日:2020-09-21

    Abstract: A sound processing method obtains note data representative of a note; obtains an audio signal to be processed; specifies, in accordance with the note, an expression sample representative of a sound expression to be imparted to the note and an expression period, of the audio signal, to which the sound expression is to be imparted to the note; and specifies, in accordance with the expression sample and the expression period, a processing parameter relating to an expression imparting processing for imparting the sound expression to a portion corresponding to the expression period in the audio signal. The method then generates a processed audio signal by performing the expression imparting processing in accordance with the expression sample, the expression period, and the processing parameter to the audio signal.

    SOUND GENERATION METHOD AND SOUND GENERATION DEVICE USING A MACHINE LEARNING MODEL

    公开(公告)号:US20240087552A1

    公开(公告)日:2024-03-14

    申请号:US18512121

    申请日:2023-11-17

    Inventor: Ryunosuke DAIDO

    CPC classification number: G10H7/002 G10H1/46 G10H7/008 G10H2210/325

    Abstract: A sound generation method includes receiving a control value at each of a plurality of time points on a time axis, accepting a mandatory instruction, generating an acoustic feature value of a specific time point, by using a trained model to process the control value and an acoustic feature value sequence, and updating the acoustic feature value sequence. The acoustic feature value sequence is updated by using the generated acoustic feature value, as the mandatory instruction has not been received for the specific time point. As the mandatory instruction has been received for the specific time point, one or more alternative acoustic feature values of one or more time points, which includes at least the specific time point, in accordance with the control value for the specific time point is generated, and the acoustic feature value sequence is updated by using the one or more alternative acoustic feature values.

    AUDIO PROCESSING METHOD AND AUDIO PROCESSING SYSTEM

    公开(公告)号:US20210256959A1

    公开(公告)日:2021-08-19

    申请号:US17306123

    申请日:2021-05-03

    Inventor: Ryunosuke DAIDO

    Abstract: An audio processing system includes a memory and a processor. The processor implements instructions to: establish a re-trained synthesis model by additional training a pre-trained synthesis model for generating feature data representative of acoustic features of an audio signal according to condition data representative of sounding conditions, using: first condition data representative of sounding conditions identified from a first audio signal of a first sound source; and first feature data representative of acoustic features of the first audio signal; receive an instruction to modify at least one of the sounding conditions of the first audio signal; generate second feature data by inputting second condition data representative of the modified at least one sounding condition into the re-trained synthesis model established by the additional training; and generate a modified audio signal in accordance with the generated second feature data.

    COMPUTER-IMPLEMENTED METHOD AND DEVICE FOR GENERATING FREQUENCY COMPONENT VECTOR OF TIME-SERIES DATA

    公开(公告)号:US20210166128A1

    公开(公告)日:2021-06-03

    申请号:US17171453

    申请日:2021-02-09

    Abstract: A computer-implemented method generates a frequency component vector of time series data, by executing a first process and a second process in each unit step. The first process includes: receiving first data; and processing the first data using a first neural network to generate intermediate data. The second process includes: receiving the generated intermediate data; and generating a plurality of component values corresponding to a plurality of frequency bands based on the generated intermediate data such that: a first component value corresponding to a first frequency band is generated using a second neural network based on the generated intermediate data; and a second component value corresponding to a second frequency band different from the first frequency band is generated using the second neural network based on the generated intermediate data and the generated first component value corresponding to the first frequency band.

    SIGNAL PROCESSING METHOD, SIGNAL PROCESSING DEVICE, AND SOUND GENERATION METHOD USING MACHINE LEARNING MODEL

    公开(公告)号:US20240029695A1

    公开(公告)日:2024-01-25

    申请号:US18472119

    申请日:2023-09-21

    Inventor: Ryunosuke DAIDO

    CPC classification number: G10H1/0025 G10H2250/311 G10H2210/111

    Abstract: A signal processing method, which is realized by a computer, includes receiving a control value representing a musical feature, receiving a selection signal for selecting either a first degree of enforcement or a second degree of enforcement that is lower than the first degree of enforcement, and generating, by using a trained model, in accordance with the selection signal, either an acoustic feature amount sequence that reflects the control value in accordance with the first degree of enforcement, or an acoustic feature amount sequence that reflects the control value in accordance with the second degree of enforcement.

    INFORMATION PROCESSING METHOD, ESTIMATION MODEL CONSTRUCTION METHOD, INFORMATION PROCESSING DEVICE, AND ESTIMATION MODEL CONSTRUCTING DEVICE

    公开(公告)号:US20220208175A1

    公开(公告)日:2022-06-30

    申请号:US17698601

    申请日:2022-03-18

    Inventor: Ryunosuke DAIDO

    Abstract: An information processing device includes a memory storing instructions, and a processor configured to implement the stored instructions to execute a plurality of tasks. The tasks includes: a first generating task that generates a series of fluctuations of a target sound based on first control data of the target sound to be synthesized, using a first model trained to have an ability to estimate a series of fluctuations of the target sound based on first control data of the target sound, and a second generating task that generates a series of features of the target sound based on second control data of the target sound and the generated series of fluctuations of the target sound, using a second model trained to estimate a series of features of the target sound based on second control data of the target sound and a series of fluctuations of the target sound.

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