Abstract: In one embodiment, a computer-implemented method includes training, using an artificial intelligence engine, one or more machine learning models using training data comprising identities of writers of content items as input and to output a dataset comprising identities of publishers and a respective probability that each identity of a publisher, from the identities of publishers, is associated with a respective identity of a writer from the identities of writers; receiving, via the one or more machine learning models, a first identity of a first writer; inputting the first identity of the first writer into the one or more machine learning models; outputting, via the one or more machine learning models, the dataset comprising the identities of publishers and the respective probability that each identity of the publisher, from the identities of publishers, is associated with the respective identity of the writer from the identities of writers.

Abstract: The disclosed systems and methods provide a novel framework that generates electronic, interactive transcripts for media, and dynamic playback capabilities via a user interface (UI) for the accompanying media. The framework generates a transcript file from an audio file, where the transcript functions as a media item itself via included deep-linking interface objects associated with detected topics, context, entities, speakers, sections, and the like. Accordingly, specific text within the transcript is selectable thereby causing search functionalities, and the transcript is segmented according to different identified speakers. The framework provides controls that enable synchronizing audio to specific terms, and portions and/or speaker tags within the transcript, which enables rendering of specific portions of the audio file directly from the transcript across terms and speakers.

Abstract: In one embodiment, a computer-implemented method is disclosed. The method includes receiving a first content item, transcribing audio included in the first content item to obtain text associated with the audio, determining a plurality of keywords included in the text, classifying, based on the plurality of keywords, the text as one or more nodes in a data structure, and ranking, based on a plurality of factors, the one or more nodes relative to one or more other nodes associated with a second content item.