Access control for on-device machine learning models

    公开(公告)号:US12204663B2

    公开(公告)日:2025-01-21

    申请号:US17241383

    申请日:2021-04-27

    Applicant: Spotify AB

    Abstract: A system and method for controlling access to an on-device machine learning model without the use of encryption is described herein. For example, a request is received from an application executing on a device of a user. The request is to download a machine learning model to the device that enables a feature of the application, and the request includes information associated with the user and/or the device. The information is used to create an obfuscation key, and a derivative model can be generated using a reference copy of the machine learning model and the obfuscation key. The derivative model and the obfuscation key are then sent to the application. When the obfuscation key is provided to the derivative model at runtime, values derived from the obfuscation key are provided as additional inputs that enable the derivative model to function properly.

    Systems and methods for embedding data in media content

    公开(公告)号:US10777177B1

    公开(公告)日:2020-09-15

    申请号:US16588470

    申请日:2019-09-30

    Applicant: Spotify AB

    Abstract: An electronic device determines a first audio event of a first media content item and modifies the first media content item by superimposing a first set of data that corresponds to the first media content item over the first audio event. The first audio event has a first audio profile configured to be presented over a first channel for playback. The first set of data has a second audio profile configured to be presented over the first channel for playback. Playback of the second audio profile is configured to be masked by the first audio profile during playback of the first media content item. The electronic device transmits, to a second electronic device, the modified first media content item.

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