Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis

With the application of an automatic scoring system to all kinds of oral English tests at all levels, the efficiency of test implementation has been greatly improved. The traditional speech signal processing method only focuses on the extraction of scoring features, which could not ensure the accura...

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Autores principales:	Ping Li, Hua Zhang, Sang-Bing Tsai
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/531afc4d85a4401a83aaea841df14c1b
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id	oai:doaj.org-article:531afc4d85a4401a83aaea841df14c1b
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spelling	oai:doaj.org-article:531afc4d85a4401a83aaea841df14c1b2021-11-08T02:35:57ZDesign of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis1607-887X10.1155/2021/3018285https://doaj.org/article/531afc4d85a4401a83aaea841df14c1b2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3018285https://doaj.org/toc/1607-887XWith the application of an automatic scoring system to all kinds of oral English tests at all levels, the efficiency of test implementation has been greatly improved. The traditional speech signal processing method only focuses on the extraction of scoring features, which could not ensure the accuracy of the scoring algorithm. Aiming at the reliability of the automatic scoring system, based on the principle of sequence matching, this paper adopts the spoken speech feature extraction method to extract the features of spoken English test pronunciation and establishes a dynamic optimized spoken English pronunciation signal model based on sequence matching, which could maintain good dynamic selection and clustering ability in a strong interference environment. According to the comprehensive experiment, the automatic scoring result of the system is much higher than that of the traditional method, which greatly improves the recognition ability of oral pronunciation, solves the difference between the automatic scoring of the system and the manual scoring, and promotes the computer automatic scoring system to replace or partially replace the manual marking.Ping LiHua ZhangSang-Bing TsaiHindawi LimitedarticleMathematicsQA1-939ENDiscrete Dynamics in Nature and Society, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mathematics QA1-939
spellingShingle	Mathematics QA1-939 Ping Li Hua Zhang Sang-Bing Tsai Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis
description	With the application of an automatic scoring system to all kinds of oral English tests at all levels, the efficiency of test implementation has been greatly improved. The traditional speech signal processing method only focuses on the extraction of scoring features, which could not ensure the accuracy of the scoring algorithm. Aiming at the reliability of the automatic scoring system, based on the principle of sequence matching, this paper adopts the spoken speech feature extraction method to extract the features of spoken English test pronunciation and establishes a dynamic optimized spoken English pronunciation signal model based on sequence matching, which could maintain good dynamic selection and clustering ability in a strong interference environment. According to the comprehensive experiment, the automatic scoring result of the system is much higher than that of the traditional method, which greatly improves the recognition ability of oral pronunciation, solves the difference between the automatic scoring of the system and the manual scoring, and promotes the computer automatic scoring system to replace or partially replace the manual marking.
format	article
author	Ping Li Hua Zhang Sang-Bing Tsai
author_facet	Ping Li Hua Zhang Sang-Bing Tsai
author_sort	Ping Li
title	Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis
title_short	Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis
title_full	Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis
title_fullStr	Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis
title_full_unstemmed	Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis
title_sort	design of automatic scoring system for oral english test based on sequence matching and big data analysis
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/531afc4d85a4401a83aaea841df14c1b
work_keys_str_mv	AT pingli designofautomaticscoringsystemfororalenglishtestbasedonsequencematchingandbigdataanalysis AT huazhang designofautomaticscoringsystemfororalenglishtestbasedonsequencematchingandbigdataanalysis AT sangbingtsai designofautomaticscoringsystemfororalenglishtestbasedonsequencematchingandbigdataanalysis
_version_	1718443184337453056

Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis

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