Machine learning model-based customized real-time sign language translation

Abstract

In various examples, machine learning model-based customized real-time sign language translation is provided. A sign language translation framework may receive a data feed and detect when translation services are needed and a particular form of sign language is being used. The framework may translate incoming spoken language into a selected sign language to be used at the client application and generate video content to display the translated sign language content to the user interface of the client application. Sign language video data may comprise a representation of an animated avatar presented as an overlay performing signing corresponding to sign language translation data. The framework may generate an augmented video feed that modifies the appearance of a meeting participant to show the participant performing the sign language translation. A translation framework may conversely translate incoming video frames depicting users using sign language into spoken language data that may be audibly presented.

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