Generating predicted ink stroke information using ink-based semantics

A system for generating predicted ink strokes comprising:

• at least one processor;
• memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising:
• receiving ink stroke data;
• inputting the ink stroke data and a semantic context into a trained machine-learning model;
• determining, from the trained machine-learning model, two or more a plurality of predicted ink strokes, wherein the determining comprises:
• generating a plurality of predicted ink strokes;
• ranking the plurality of predicted ink strokes based on semantic context;
• and
• selecting the two or more predicted ink strokes from the plurality of predicted ink strokes, based on the ranking;
• and
• generating a plurality of indications that each correspond to a different predicted ink stroke from the two or more predicted ink strokes;
• receiving a selection of one of the plurality of indications;
• and
• updating the trained model based on the selection, the input ink stroke data, and the input semantic context, to accommodate a specific user.

A method for generating predicted ink strokes, the method comprising:

• receiving ink stroke data, wherein the received ink stroke data comprises information corresponding to penmanship cleanliness;
• inputting the ink stroke data and a semantic context into a trained machine-learning model;
• determining, from the trained machine learning model, a predicted ink stroke, wherein the determining comprises:
• generating a plurality of predicted ink strokes;
• sorting the plurality of predicted ink strokes based on the semantic context;
• and
• selecting the predicted ink stroke from the plurality of predicted ink strokes, based on the sorting;
• and
• generating an indication of the predicted ink stroke, based on the penmanship cleanliness.