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:
Feb. 22, 2022

Filed:

Aug. 21, 2019
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Dimitrios Basile Dimitriadis, Bellevue, WA (US);

Xie Chen, Bellevue, WA (US);

Nanshan Zeng, Bellevue, WA (US);

Yu Shi, Bellevue, WA (US);

Liyang Lu, Redmond, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/00 (2013.01); G10L 15/16 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G10L 15/18 (2013.01); G10L 15/197 (2013.01); G10L 15/22 (2006.01);
U.S. Cl.
CPC ...
G10L 15/16 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G10L 15/1815 (2013.01); G10L 15/197 (2013.01); G10L 15/22 (2013.01); G10L 2015/223 (2013.01);
Abstract

According to some embodiments, a multi-layer speech recognition transcript post processing system may include a data-driven, statistical layer associated with a trained automatic speech recognition model that selects an initial transcript. A rule-based layer may receive the initial transcript from the data-driven, statistical layer and execute at least one pre-determined rule to generate a first modified transcript. A machine learning approach layer may receive the first modified transcript from the rule-based layer and perform a neural model inference to create a second modified transcript. A human editor layer may receive the second modified transcript from the machine learning approach layer along with an adjustment from at least one human editor. The adjustment may create, in some embodiments, a final transcript that may be used to fine-tune the data-driven, statistical layer.


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