Abstract: A training data system enables the generation of training data based on video content received from one or more outside video sources. For example, the generated training data can include a transcript of a word or phrase alongside emotion, language style, and brand perception data associated with that word or phrase. To generate the training data from a video, the subtitles, video frame, metadata, and audio levels of the video can be analyzed by the training data system. The generated training data (potentially from a plurality of videos) can then be grouped into a set of training data and used to train machine learning modules for Natural Language Processing (NLP) techniques.

Abstract: A training data system enables the generation of training data based on video content received from one or more outside video sources. For example, the generated training data can include a transcript of a word or phrase alongside emotion, language style, and brand perception data associated with that word or phrase. To generate the training data from a video, the subtitles, video frame, metadata, and audio levels of the video can be analyzed by the training data system. The generated training data (potentially from a plurality of videos) can then be grouped into a set of training data and used to train machine learning modules for Natural Language Processing (NLP) techniques.

Abstract: A remote localization server enables application or website developers to revise and update presentation content for different target localities without having to reprogram an application for each locality. Such presentation content can include, for example, text, images, audio/video, and user interface (“UI”) elements. The updated content can then be synchronized (i.e., “pushed”) in real-time, in a remote fashion, to apps installed and running on end user devices, allowing app developers to be agile and responsive to the dynamic demands of a growing user base.

Abstract: An adaptive localization system translates and displays translated content to a user, for example through a website or application using the adaptive localization system. A user can view, receive, or otherwise interact with the translated content, which can be differently translated based on desired language, geographic location, an intended user, or other relevant characteristics of the viewing user. The adaptive localization engine can translate the inherent meaning of content rather than, for example, creating an exact grammatical or “word-for-word” translation of individual words or phrases in the content. The adaptive localization engine displays alternate variations of the same translation of content to different users and based on user response to the alternate translations, determines the accuracy or correctness of a certain translations of content and modifies future translations accordingly.

Abstract: An adaptive localization system translates and displays translated content to a user, for example through a website or application using the adaptive localization system. A user can view, receive, or otherwise interact with the translated content, which can be differently translated based on desired language, geographic location, an intended user, or other relevant characteristics of the viewing user. The adaptive localization engine can translate the inherent meaning of content rather than, for example, creating an exact grammatical or “word-for-word” translation of individual words or phrases in the content. The adaptive localization engine displays alternate variations of the same translation of content to different users and based on user response to the alternate translations, determines the accuracy or correctness of a certain translations of content and modifies future translations accordingly.