Non-Scorable Response Filters for Speech Scoring Systems

Patent №

US 9,704,413

Granted

2017-07-11

Filed 2015

Owner

EDUCATIONAL TESTING SERVICE

Lab

AI components

5

ml · nlp · speech · kr · planning

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

14665258

A method for scoring non-native speech includes receiving a speech sample spoken by a non-native speaker and performing automatic speech recognition and metric extraction on the speech sample to generate a transcript of the speech sample and a speech metric associated with the speech sample. The method further includes determining whether the speech sample is scorable or non-scorable based upon the transcript and speech metric, where the determination is based on an audio quality of the speech sample, an amount of speech of the speech sample, a degree to which the speech sample is off-topic, whether the speech sample includes speech from an incorrect language, or whether the speech sample includes plagiarized material. When the sample is determined to be non-scorable, an indication of non-scorability is associated with the speech sample. When the sample is determined to be scorable, the sample is provided to a scoring model for scoring.

Machine learningNatural languageSpeechKnowledge representationPlanningG09B 19/06G10L 15/005G10L 15/01G10L 15/26G10L 25/60G10L 25/78G10L 25/90

AI classification

Natural language1.00
Speech1.00
Machine learning1.00
Knowledge representation0.90
Planning0.82
AI hardware0.01
Vision0.01
Evolutionary computation0.00

Ownership

EDUCATIONAL TESTING SERVICE

assignment · 365180954

Assignors

YOON, SU-YOUN, HIGGINS, DERRICK, ZECHNER, KLAUS, XIE, SHASHA, JEON, JE HUN, EVANINI, KEELAN, LING, GUANGMING, BEJAR, ISAAC

On an employer assignment, the assignors are typically the inventors.

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