Modality-expanding gaming experience

Abstract

Systems and methods are disclosed for expanding the output modalities of a gameplay session. Gameplay input data, such as audio data, video data, haptics data, and Gameplay context data, can be processed using machine learning (ML) models to generate output state vectors, which can be used to drive state changes in remote devices, such as smarthome devices (e.g., smart lightbulbs, smart light switches, smart fans, smart thermostats, smart blinds, smart speakers, etc.). To generate the output state vectors, first gameplay features are extracted from the gameplay input data, then the gameplay features are processed by a state vector generation model to generate the state vectors. Each modality of gameplay input data can be processed by a corresponding feature extractor. Gameplay sessions can be evaluated to train the ML models.