IDiyas

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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 11842524 B1

PDFFull Text
Date of Patent:
Dec. 12, 2023

Filed:

Apr. 30, 2021

Multi-modal learning based intelligent enhancement of post optical character recognition error correction

Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Rajesh M. Desai, San Jose, CA (US);

Ayush Utkarsh, Ranchi, IN;

Nazrul Islam, San Jose, CA (US);

Praveen Vyas, Behind Indan Gas Godown, IN;

Assignee:

International Business Machines Corporation, Armonk, NY (US);

Attorneys:

Stephen J. Walder, Jr.

Matt Zebrec

Primary Examiner:

Eric Rush

Int. Cl.
CPC ...
G06K 9/03 (2006.01); G06V 10/40 (2022.01); G06F 40/126 (2020.01); G06F 40/109 (2020.01); G06N 20/00 (2019.01); G06F 40/232 (2020.01); G06V 30/10 (2022.01); G06F 18/214 (2023.01); G06V 30/19 (2022.01); G06V 30/12 (2022.01); G06V 10/82 (2022.01); G06V 30/26 (2022.01); G06F 18/213 (2023.01); G06N 3/0464 (2023.01); G06N 3/0442 (2023.01); G06N 3/0455 (2023.01); G06V 10/98 (2022.01); G06F 40/279 (2020.01); G06V 30/242 (2022.01);
U.S. Cl.
CPC ...
G06V 10/40 (2022.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 40/109 (2020.01); G06F 40/126 (2020.01); G06F 40/232 (2020.01); G06F 40/279 (2020.01); G06N 3/0442 (2023.01); G06N 3/0455 (2023.01); G06N 3/0464 (2023.01); G06N 20/00 (2019.01); G06V 10/82 (2022.01); G06V 10/98 (2022.01); G06V 30/10 (2022.01); G06V 30/12 (2022.01); G06V 30/19 (2022.01); G06V 30/242 (2022.01); G06V 30/26 (2022.01);
Abstract

A mechanism is provided for implementing an optical character recognition (OCR) error correction mechanism for correcting OCR errors. Responsive to receiving a document in which OCR has been performed, the mechanism assesses the document to identify a set of OCR errors generated by an OCR engine that performed the OCR using a set of visual embeddings. Responsive to identifying the set of OCR errors, the mechanism analyzes each character of a plurality of sentences within the document to generate a high-dimensional embedding for the characters of the plurality of sentences within the document. The mechanism then linguistically corrects each OCR error in the set of OCR error. The mechanism utilizes ground truth information and the set of visual embeddings to verify that character stream is linguistically correct. Responsive to verifying that the character stream is linguistically correct, the mechanism outputs an OCR error corrected document to a user.

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