This disclosure describes techniques for handwriting recognition for Unicode text entered via touch or other input. For example, Unicode text may be part of program source code in some programming languages. The handwritten code is provided as an input to a trained machine learning model. The model produces possible matches for the user entered text along with a score for each match. The user, e.g., a programmer, can select the appropriate match which is then added to the source code. The model is trained with sample handwritten text for known programs, and can also utilize additional factors such as program context and handwriting stroke information. The techniques can be implemented in IDE software, operating systems, and in devices that enable such input, e.g., electronic whiteboards.
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Luszczyk, Michal and Feuz, Sandro, "Handwriting recognition for IDEs with Unicode support", Technical Disclosure Commons, (December 11, 2017)