CPC G06F 40/109 (2020.01) [G06F 40/169 (2020.01); G06N 3/02 (2013.01)] | 20 Claims |
1. A computer-implemented method comprising:
receiving a selection of text;
providing the selection of text to a font recommendation model trained to predict a font recommendation by learning associations between visual attributes of a plurality of font types and verbal contexts of training texts;
generating, by the font recommendation model, an embedding representing a verbal context of the selection of text, the verbal context of the selection of text including emotions conveyed by the selection of text;
generating, by the font recommendation model, a prediction score for each of the plurality of font types based on the embedding representing the verbal context of the selection of text, wherein each prediction score is based on a relationship between visual attributes of a corresponding font type and the emotions conveyed by the selection of text, wherein a higher prediction score for a font type indicates greater congruency between the font type and the emotions conveyed by the selection of text; and
returning at least one recommended font type based on the prediction score for each of the plurality of font types.
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