US 12,080,089 B2
Enhancing machine translation of handwritten documents
Barton Wayne Emanuel, Manassas, VA (US); Nadiya Kochura, Bolton, MA (US); Su Liu, Austin, TX (US); and Tetsuya Shimada, Seattle, WA (US)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Dec. 8, 2021, as Appl. No. 17/643,227.
Prior Publication US 2023/0177858 A1, Jun. 8, 2023
Int. Cl. G06V 30/414 (2022.01); G06F 16/93 (2019.01); G06F 40/58 (2020.01); G06V 30/22 (2022.01); G06V 30/413 (2022.01)
CPC G06V 30/414 (2022.01) [G06F 16/93 (2019.01); G06F 40/58 (2020.01); G06V 30/22 (2022.01); G06V 30/413 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for enhancing machine translation of a document, the method comprising:
capturing an image of the document, wherein the document includes a plurality of characters that are arranged in a character layout;
classifying the image by a document type using a machine learning classification model based on the character layout, wherein the machine learning classification model is trained using a plurality of training documents stored in a knowledge corpus;
determining a strategy for an intelligent character recognition (ICR) algorithm with the image based on the character layout; and
generating a translated document by applying the intelligent character recognition (ICR) algorithm to the plurality of characters in the image using the strategy, wherein the translated document includes a plurality of translated characters that are arranged in the character layout.