Calibration optimization method and system for speaking test evaluation

Abstract

The invention discloses a calibration optimization method and system for speaking test evaluation. The method includes the steps of selecting part of all voice data corresponding to question types to be calibrated to serve as calibration voice data, conducting manual annotation by calibration specialists, obtaining the manual annotation result of the manually-annotated calibration voice data, conducting voice recognition on the calibration voice data through a voice recognition system, extracting evaluation characteristics of different characteristic types corresponding to evaluation standards of the question types to be calibrated from the voice recognition result of the calibration voice data, and training and optimizing existing marking models corresponding to the question types to be calibrated through the combination of the evaluation characteristics and the manual annotation result of the calibration voice data so as to obtain new marking models. Due to the fact that the existing marking models are optimized through the manual annotation result, the new marking models can be matched with the marking standards of existing speaking tests as much as possible, and the better marking performance can be presented when the speaking test evaluation is conducted through the new marking models obtained through the method.

Description

technical field [0001] The invention relates to the technical field of speech signal processing, in particular to a method and system for optimizing calibration standards of oral exams. Background technique [0002] With the development and maturity of speech recognition technology, intelligent speech evaluation technology involving speech technology, natural language understanding, artificial intelligence, data mining, machine learning, etc. It has been widely used in other application scenarios. Especially in large-scale oral tests in various languages, in order to reduce test costs, improve test scoring efficiency, reduce subjective differences among different raters, and ensure test fairness, intelligent voice evaluation technology has played a major role, and gradually Instead of manual oral evaluation, for example, in the national Putonghua proficiency test, the Jiangsu high school entrance examination oral English test, and the Guangdong college entrance examination ...

AI Technical Summary

Problems solved by technology

[0013] The embodiment of the present invention aims at the problem of poor scoring performance when the general scoring model in the existing oral test evaluation method cannot match the current oral test scoring standard, and proposes an oral test evaluation based on manual calibration Calibration optimization method and system for

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