Abstract: A method is provided for modifying a first media content item by superimposing a first set of data over a first audio event having an amplitude that satisfies a first threshold. The first audio event has a first audio profile, the first set of data has a second audio profile, playback of the second audio profile is configured to be masked by the first audio profile during playback of the first media content item, and the first set of data includes playlist information. The method includes transmitting, to a second electronic device, the modified first media content item.

Abstract: A method includes displaying a user interface of a digital audio workstation, which includes a composition region for generating a composition. The composition region includes a representation of a first MIDI file that has already been added to the composition by a user. The method further includes receiving a user input to import, into the composition region, an audio file. In response to the user input to import the audio file, the method includes importing the audio file, which includes, without user intervention, aligning the audio file with a rhythm of the first MIDI file, modifying a rhythm of the audio file based on the rhythm of the first MIDI file, and displaying a representation of the audio file in the composition region.

Abstract: An electronic device modifies a first media content item by superimposing a first set of data over a first accented musical event. The first accented musical event has a first audio profile. The first set of data has a second audio profile 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.

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.

Abstract: An electronic device modifies a first media content item by superimposing a first set of data over a first accented musical event. The first accented musical event has a first audio profile. The first set of data has a second audio profile 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.

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.