Netflix patents method to filter out inconsistent raters in video quality tests
Netflix has been granted a patent for a software tool that improves the accuracy of subjective video quality experiments. The system uses mathematical models to identify participants who give inconsistent scores and excludes them from future testing rounds.
In the filing’s own words
In various embodiments, a data optimization application mitigates scoring inaccuracies in subjective quality experiments. In operation, the data optimization application generates a model that includes a first set of individual scores and a first set of parameters. The first set of parameters includes a first subjective score set and a first set of subjective factor sets. The data optimization application performs one or more optimization operations on the first set of parameters to generate a second set of parameters. The second set of parameters includes a second subjective score set and a second set of subjective factor sets, wherein the second subjective score set compensates for at least a first subjective factor set included in the second set of subjective factor sets. The data optimization application also computes a participant evaluation report based on at least a second subjective factor sets included in the second set of subjective factor sets
What exactly they claim (claim 1)
1. A computer-implemented method for mitigating scoring inaccuracies in subjective quality experiments, the method comprising: performing, via a propagation solver, a plurality of iterative operations to update a first plurality of parameters of a model that includes a plurality of individual scores assigned by a plurality of participants during a first experiment round to generate a first subjective factor set comprising a different participant inconsistency for each participant in the plurality of participants, wherein performing the plurality of iterative operations includes generating a maximum likelihood estimation formulation of the model and executing the propagation solver to automatically compute a solution for the maximum likelihood estimation formulation to generate the first subjective factor set comprising initiating an update rule generator to generate a set of update rules for updating the first plurality of parameters, and iteratively initiating a propagation engine to iteratively update the first plurality of parameters based on the set of update rules and a refresh rate until a stop threshold is satisfied to generate an optimized plurality of parameters for the model that comprises the solution for the maximum likelihood estimation formulation, wherein the first subjective factor set optimized plurality of parameters corresponds to the first subjective factor set; computing a ranking of the plurality of participants with respect to each other based on the first subjective factor set; and generating a participant evaluation report that includes information indicating a portion of the plurality of participants that, based on the ranking of the plurality of participants with respect to each other, meet a participant inconsistency criterion for exclusion from a second experiment round during which the plurality of participants less the portion of the plurality of participants assign one or more additional individual scores, wherein the participant inconsistency criterion specifies a predefined number of participants included in the plurality of participants that are associated with highest participant consistencies.
Facts
- Company
- Netflix (NETFLIX, INC.)
- Official title
- Techniques for increasing the accuracy of subjective quality experiments
- Patent number
- US12764302B2
- Application number
- 17840544
- Filed
- Jun 14, 2022
- Granted
- Oct 13, 2026
- Inventors
- 1
- Claims
- 19
Classified under
H04N 19/149 Electricity & electronicsG06Q 30/0203 Physics & computingH04L 65/80 Electricity & electronicsH04N 19/154 Electricity & electronicsMore from Netflix in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.
