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:
Feb. 11, 2020

Filed:

May. 24, 2018
Applicant:

Educational Testing Service, Princeton, NJ (US);

Inventors:

Jidong Tao, Lawrenceville, NJ (US);

Lei Chen, Lawrenceville, NJ (US);

Chong Min Lee, Pennington, NJ (US);

Assignee:

Educational Testing Service, Princeton, NJ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/00 (2013.01); G09B 19/04 (2006.01); G06N 3/04 (2006.01); G10L 15/183 (2013.01); G10L 15/16 (2006.01);
U.S. Cl.
CPC ...
G09B 19/04 (2013.01); G06N 3/04 (2013.01); G10L 15/16 (2013.01); G10L 15/183 (2013.01);
Abstract

Provide automatic assessment of oral recitations during computer based language assessments using a trained neural network to automate the scoring and feedback processes without human transcription and scoring input by automatically generating a score of a language assessment. Providing an automatic speech recognition ('ASR') scoring system. Training multiple scoring reference vectors associated with multiple possible scores of an assessment, and receiving an acoustic language assessment response to an assessment item. Based on the acoustic language assessment automatically generating a transcription, and generating an individual word vector from the transcription. Generating an input vector by concatenating an individual word vector with a transcription feature vector, and supplying an input vector as input to a neural network. Generating an output vector based on weights of a neural network; and generating a score by comparing an output vector with scoring vectors.


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