Microsoft Technology Licensing, LLC

Tao Ge

Tomasz Lukasz Religa

Max Wang

Huitian Jiao

Si-Qing Chen

Lei Cui

Furu Wei

Kaushik Ramaiah Narayanan

Zhang Li

Xun Wang

Jesse Alexander Freitas

Ravi Mandliya

Warren Anthony Aldred

Utsab Bose

A data processing system obtains source textual content associated with a first writing style and target textual content associated with a second writing style and provides the source textual content as an input to a first machine learning model which analyzes the source content to determine the first writing style of the first textual content. The system provides an indication of the first writing style and the target textual content as an input to a second machine learning model which analyzes the target textual content and rewrites the target textual content according to the first writing style to output updated target textual content rewritten according to the first writing style. Some implementations utilize a single model trained to receive the source textual content, the target textual content, to determine the writing style of the source textual content and rewrite the target textual content according to the first writing style.

Automatic writing style detection and rewriting

A system and method for converting a document is described. The system accesses a document comprising one or more section breaks. The system detects sections of the text document demarked by the one or more section breaks and generates a section title metadata and a section summary metadata for each section of the plurality of sections. The system inserts the section title metadata and the section summary metadata at the corresponding section breaks in the text document. The system modifies the text document into slides. Each slide being formed for each section based on the corresponding section title metadata and the section summary metadata. The system generates a presentation document based on the slides.

Document conversion engine

Growing community of inventors

Beijing, China

Tao Ge