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. 02, 2025

Filed:

Jun. 18, 2020
Applicant:

Netflix, Inc., Los Gatos, CA (US);

Inventors:

Chih-Wei Wu, Los Gatos, CA (US);

Phillip A. Williams, Los Gatos, CA (US);

William Francis Wolcott, Iv, Los Gatos, CA (US);

Assignee:

NETFLIX, INC., Los Gatos, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G10L 25/60 (2013.01); G06F 17/18 (2006.01); G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G10L 25/27 (2013.01);
U.S. Cl.
CPC ...
G10L 25/60 (2013.01); G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G10L 25/27 (2013.01); G06F 17/18 (2013.01);
Abstract

In various embodiments, a training application trains a multitask learning model to assess perceived audio quality. The training application computes a set of pseudo labels based on a first audio clip and multiple models. The set of pseudo labels specifies metric values for a set of metrics that are relevant to audio quality. The training application also computes a set of feature values for a set of audio features based on the first audio clip. The training application trains a multitask learning model based on the set of feature values and the set of pseudo labels to generate a trained multitask learning model. In operation, the trained multitask learning model maps different sets of feature values for the set of audio features to different sets of predicted labels. Each set of predicted labels specifies estimated metric values for the set of metrics.


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