Roku, Inc.

Brian Thoft Moth MØller

Jan Neerbek

Paul Nangeroni

Amalavoyal Narasimha Chari

Kasper Andersen

Paul Fleischer

Rafal Krzysztof Malewski

Bjørn Reese

Disclosed herein are various embodiments for implementing audio enhancements based on video detection. An embodiment operates by receiving an audio clip corresponding to a video clip to be output simultaneously. The video clip is classified as belonging to a video category. An enhancement of the audio clip is determined based on crowd-sourced responses to the video category. The audio clip is configured in accordance with the enhancement. The configured audio clip is provided to the audio output device to audibly output with the enhancement.

Audio enhancements based on video detection

Disclosed herein are system, method, and computer program product embodiments for synchronizing playback of an audio and/or video content. An embodiment operates by collectively selecting, by a first device in concert with a second device of a plurality of devices in a computer network session, and in accordance with a predetermined synchronization list comprising a first and second synchronization mechanism, the first synchronization mechanism over the second synchronization mechanism such that the first synchronization mechanism is more precise than the second synchronization mechanism. The first and second synchronization mechanisms are configured to provide a synchronized playback of the at least one of the audio content and the video content.

Audio time synchronization using prioritized schedule

Disclosed herein are system, method, and computer program product embodiments for detecting human presence in front of a plurality of sensors, such as speaker sensors, and a device with a processor, such as a television. An example method includes varying, during a collection routine, a respective signal strength of one or more of a plurality of transmitters. The example method further includes receiving results of the collection routine in a form of raw data from a plurality of sensors. The example method further includes determining, by at least one processor, a respective geographical position of one or more humans present within a predetermined geographical range of the at least one processor based on the raw data from the plurality of sensors. Subsequently, the example method includes executing an action based on the respective geographical position of the one or more humans.

Providing customized entertainment experience using human presence detection

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Hojberg, Denmark

Brian Thoft Moth MØller