Method and system for testing comprehensive vocabulary ability by combining spelling and pronunciation

By collecting spelling and pronunciation data, a dynamic cognitive state matrix is ​​constructed to analyze the network instability risk of high-risk words and their related words. This solves the problem that existing technologies cannot assess the depth of mastery of word sound-spelling correspondence rules, and enables accurate assessment and systematic early warning of comprehensive vocabulary ability.

CN122174831APending Publication Date: 2026-06-09BEIJING TUOCI INTELLIGENT TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202610284163.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-10
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

Existing technologies cannot effectively assess learners' mastery of the rules of word sound-spell correspondence, nor can they diagnose systemic cognitive weaknesses. They sever the intrinsic connection between spelling and pronunciation and ignore learners' cognitive processing behavior during the answering process.

Method used

By collecting bimodal data on spelling and pronunciation, calculating bimodal mastery values ​​and correction costs, constructing a dynamic cognitive state matrix, analyzing the network instability risk of high-risk words and their related words, and generating a diagnostic report.

Benefits of technology

It enables accurate assessment of comprehensive vocabulary ability, identifies core weaknesses, provides early warning of systemic errors, and offers a visualized cognitive state mapping.

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Abstract

The invention discloses a spelling and pronunciation combined vocabulary comprehensive ability test method and system, and relates to the technical field of data processing, and the method comprises the steps: collecting spelling data, voice data and correction operation data of a user for a target vocabulary; calculating a bimodal mastering value of each target vocabulary based on the spelling data and the voice data, and calculating a correction cost value of each target vocabulary based on the correction operation data; mapping each target vocabulary to a dynamic cognitive state matrix, and marking the vocabulary of which the bimodal mastering value is lower than a first threshold value and the correction cost value is higher than a second threshold value as a high-risk vocabulary; if the bimodal mastering value of the associated vocabularies exceeding the preset proportion in the associated vocabularies of the high-risk vocabularies is reduced or the correction cost value is increased, determining that a vocabulary network instability risk formed by the high-risk vocabularies and the associated vocabularies thereof exists; and generating a diagnosis report according to the dynamic cognitive state matrix and the judgment result of the vocabulary network instability risk.
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