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:
Sep. 15, 2026

Filed:

Feb. 26, 2024
Applicant:

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

Inventors:

Shubham Bansal, Hyderabad, IN;

Vikas Joshi, Bengaluru, IN;

Rishon Dsouza, Bangalore, IN;

Rupeshkumar Rasiklal Mehta, Hyderabad, IN;

Harveen Singh Chadha, Bangalore, IN;

Arijit Mukherjee, Hyderabad, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/45 (2020.01); G06F 40/58 (2020.01); G10L 15/22 (2006.01);
U.S. Cl.
CPC ...
G06F 40/58 (2020.01); G10L 15/22 (2013.01); G10L 2015/227 (2013.01);
Abstract

A technique translates speech in a first language to text in a second language manner in a manner that is appropriate for the gender of the speaker. In some implementations, the technique receives an input setting that specifies one of three translation modes: masculine mode, feminine mode, and auto mode. The first two modes produce translations in masculine and feminine modes by default, respectively, while the auto mode produces translations in forms that are based on the detected characteristics of audio signals. According to some implementations, the technique uses a training framework that automatically converts a corpus of training examples that exhibit gender bias (e.g., a male gender bias) to training examples having a reducing incidence of gender bias. In some implementations, the training framework updates weights of the machine-trained model based on a combination of two loss components: translation loss and gender loss.


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