Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning Machine

This paper proposes a feature extraction algorithm based on the maximum entropy phrase reordering model in statistical machine translation in language learning machines. The algorithm can extract more accurate phrase reordering information, especially the feature information of reversed phrases, whi...

Full description

Saved in:
Bibliographic Details
Main Author: Weifang Wu
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/6662088
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832554586001375232
author Weifang Wu
author_facet Weifang Wu
author_sort Weifang Wu
collection DOAJ
description This paper proposes a feature extraction algorithm based on the maximum entropy phrase reordering model in statistical machine translation in language learning machines. The algorithm can extract more accurate phrase reordering information, especially the feature information of reversed phrases, which solves the problem of imbalance of feature data during maximum entropy training in the original algorithm, and improves the accuracy of phrase reordering in translation. In the experiment, they were combined with linguistic features such as parts of speech, words, and syntactic features extracted by using the syntax analyzer, and the maximum entropy classifier was used to predict translation errors, and the experimental verification was performed on the Chinese-English translation data set and compared. The experimental results show that different word posterior probabilities have a significant impact on the classification error rate, and the combination of linguistic features based on the word posterior probability can significantly reduce the classification error rate and improve the translation error prediction performance.
format Article
id doaj-art-a8b382465918455d8b412d66df01c478
institution Kabale University
issn 1076-2787
1099-0526
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-a8b382465918455d8b412d66df01c4782025-02-03T05:51:11ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/66620886662088Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning MachineWeifang Wu0Department of Foreign Language, Anhui Jianzhu University, Hefei 230601, ChinaThis paper proposes a feature extraction algorithm based on the maximum entropy phrase reordering model in statistical machine translation in language learning machines. The algorithm can extract more accurate phrase reordering information, especially the feature information of reversed phrases, which solves the problem of imbalance of feature data during maximum entropy training in the original algorithm, and improves the accuracy of phrase reordering in translation. In the experiment, they were combined with linguistic features such as parts of speech, words, and syntactic features extracted by using the syntax analyzer, and the maximum entropy classifier was used to predict translation errors, and the experimental verification was performed on the Chinese-English translation data set and compared. The experimental results show that different word posterior probabilities have a significant impact on the classification error rate, and the combination of linguistic features based on the word posterior probability can significantly reduce the classification error rate and improve the translation error prediction performance.http://dx.doi.org/10.1155/2020/6662088
spellingShingle Weifang Wu
Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning Machine
Complexity
title Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning Machine
title_full Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning Machine
title_fullStr Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning Machine
title_full_unstemmed Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning Machine
title_short Model and Simulation of Maximum Entropy Phrase Reordering of English Text in Language Learning Machine
title_sort model and simulation of maximum entropy phrase reordering of english text in language learning machine
url http://dx.doi.org/10.1155/2020/6662088
work_keys_str_mv AT weifangwu modelandsimulationofmaximumentropyphrasereorderingofenglishtextinlanguagelearningmachine