Grammarly, Inc.

Megan Keough

Mark Norris

Jennifer Van Dam

Maxim Gubin

Alice Shen

Dmitry Unkovsky

Yevhen Bochkov

Oleksandr Korniienko

Yuriy Tanskyi

Lily Ng

In one embodiment, the disclosure provides a computer-implemented method, comprising receiving, by a computer system, electronic digital data representing a first text sequence in a first language, the first text sequence comprising unstructured natural language text; by one or more machine-learning models of the computer system, determining a score corresponding to the first text sequence, the score being determined by one or more rule-based filters and indicating one or more predicted tones; determining whether to modify the first text sequence based on the score of the first text sequence; in response to a determination to modify the first text sequence, modifying the first text sequence, the modifying comprising replacement of at least one or more words of the first text sequence to result in creating and digitally storing a second text sequence; and transmitting a graphical control element indicative of a tone associated with the second text sequence for display.

Rewriting tone of natural language text

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Beacon, NY, United States of America

Megan Keough