US 12,112,134 B2
Methods for emotion classification in text
Dana Movshovitz-Attias, Mountain View, CA (US); John Patrick McGregor, Jr., Mountain View, CA (US); Gaurav Nemade, Mountain View, CA (US); Sujith Ravi, Santa Clara, CA (US); Jeongwoo Ko, Mountain View, CA (US); and Dora Demszky, Stanford, CA (US)
Assigned to GOOGLE LLC, Mountain View, CA (US)
Filed by Google LLC, Mountain View, CA (US)
Filed on Jan. 24, 2022, as Appl. No. 17/582,206.
Claims priority of provisional application 63/161,275, filed on Mar. 15, 2021.
Prior Publication US 2022/0292261 A1, Sep. 15, 2022
Int. Cl. G06F 40/289 (2020.01); G06F 40/30 (2020.01); G06N 20/00 (2019.01)
CPC G06F 40/289 (2020.01) [G06F 40/30 (2020.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method of training a computer-implemented emotion classification model, the method comprising:
retrieving, from a database, training data for a text-based application;
extracting from the training data, by one or more processors, a set of phrases that are associated with a set of taxonomy concepts;
extracting from the set of phrases, by the one or more processors, a set of emotion examples based on emotion-bearing phrases in the set of phrases; and
training, by the one or more processors, the emotion classification model based on a set of emotion-bearing phrases, wherein the trained emotion classification model associates one or more graphical indicia with at least one of a sender or a recipient of the text-based application.