Invention Grant
- Patent Title: Techniques for computing perceived audio quality based on a trained multitask learning model
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Application No.: US16905810Application Date: 2020-06-18
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Publication No.: US11636872B2Publication Date: 2023-04-25
- Inventor: Chih-Wei Wu , Phillip A. Williams , William Francis Wolcott, IV
- Applicant: NETFLIX, INC.
- Applicant Address: US CA Los Gatos
- Assignee: NETFLIX, INC.
- Current Assignee: NETFLIX, INC.
- Current Assignee Address: US CA Los Gatos
- Agency: Artegis Law Group, LLP
- Main IPC: G10L25/60
- IPC: G10L25/60 ; G10L25/27 ; G06K9/62 ; G06N20/00 ; G06F17/18
Abstract:
In various embodiments, a quality inference application estimates perceived audio quality. The quality inference application computes a set of feature values for a set of audio features based on an audio clip. The quality inference application then uses a trained multitask learning model to generate predicted labels based on the set of feature values. The predicted labels specify metric values for metrics that are relevant to audio quality. Subsequently, the quality inference application computes an audio quality score for the audio clip based on the predicted labels.
Public/Granted literature
- US20210350820A1 TECHNIQUES FOR COMPUTING PERCEIVED AUDIO QUALITY BASED ON A TRAINED MULTITASK LEARNING MODEL Public/Granted day:2021-11-11
Information query
