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:
Jun. 30, 2026

Filed:

Sep. 25, 2023
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Yunlong Jiao, Hatfield, GB;

Anisha Garg, Seattle, WA (US);

Emine Yilmaz, London, GB;

Gabriella Kazai, Bishops Stortford, GB;

Liu Yang, Seattle, WA (US);

Wenbo Yan, Redmond, WA (US);

Liane Lewin-Eytan, Binyamina, IL;

Prathap Ramachandra, Kirkland, WA (US);

Prasanna Soundararajan, Redmond, WA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/06 (2013.01); G10L 15/26 (2006.01);
U.S. Cl.
CPC ...
G10L 15/063 (2013.01); G10L 15/26 (2013.01); G10L 2015/0638 (2013.01);
Abstract

Techniques for training and testing machine learning models using biased samples are described. In some examples, a sampled test set is generated by estimating a propensity score for each annotation of the set of annotations, wherein a propensity score quantifies a likelihood of being human generated using the set of data, estimating a confidence score for each annotation of the set of annotations, wherein a confidence score quantifies a confidence in a correctness of the annotation, mapping each annotation of the set of annotations to a multi-dimensional space based at least in part on the propensity score, stratifying, based on the propensity score, the mapped annotations, and sampling each stratum according to a request to generate a sampled test set.


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