Abstract: 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.

Abstract: A computer-implemented process is programmed to detect a type or category of document that is being drafted and to suggest one or more phrases or sentences to add to the original and/or substitute for the original, the suggested text being potentially more personable and sincere than the writer’s original text. Suggested text phrases are selected from a large corpus of previously manually drafted sentences and phrases. Selected text phrases are ranked and filtered to result in suggesting a manageable set of text phrases. With this approach, adding specially chosen content to existing content can change the warmth or tone of the text while preserving its meaning. Unlike prior approaches, in an embodiment, the process is programmed to artificially understand the intent of the original text as a basis of suggesting other content to add.