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.

Date of Patent:
Apr. 30, 2024

Filed:

Dec. 02, 2020
Applicant:

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

Inventors:

Shikhar Kwatra, San Jose, CA (US);

Vijay Ekambaram, Chennai, IN;

Hemant Kumar Sivaswamy, Pune, IN;

Rodrigo Goulart Silva, Raleigh, NC (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G10L 15/19 (2013.01); G06V 10/40 (2022.01); G06V 20/40 (2022.01); G06V 30/10 (2022.01); G10L 15/10 (2006.01); G10L 15/18 (2013.01); G10L 15/22 (2006.01); H04N 21/439 (2011.01); H04N 21/44 (2011.01);
U.S. Cl.
CPC ...
G10L 15/19 (2013.01); G06V 10/40 (2022.01); G06V 20/41 (2022.01); G06V 30/10 (2022.01); G10L 15/10 (2013.01); G10L 15/1815 (2013.01); G10L 15/22 (2013.01); H04N 21/4394 (2013.01); H04N 21/44008 (2013.01);
Abstract

Mitigating mistranscriptions resolves errors in a transcription of the audio portion of a video based on a semantic matching with contextualized data electronically garnered from one or more sources other than the audio portion of the video. A mistranscription is identified using a pretrained word embedding model that maps words to an embedding space derived from the contextualizing data. A similarity value for each vocabulary word of a multi-word vocabulary of the pretrained word embedding model is determined in relation to the mistranscription. Candidate words are selected based on the similarity values, each indicating a closeness of a corresponding vocabulary word to the mistranscription. The textual rendering is modified by replacing the mistranscription with a candidate word that, based on average semantic similarity values, is more similar to the mistranscription than is each other candidate word.


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