College English Translation Intelligent Systems Technology Based on Multi-Source Information Corpus Acquisition and Data Fusion

Authors

  • Wentao Meng Department of Basic Education, Beihai Campus, Guilin University of Electronic Technology, Beihai 536000, China
  • Lei Yu School of Sports and Arts, Harbin Sport University, Harbin 230000, China
  • Yunyun Zhu Department of Economics and Management, Beihai Campus, Guilin University of Electronic Technology, Beihai 536000, China

Abstract

Translation scenarios for college English are moving in interdisciplinary and cross-disciplinary directions, meaning that traditional methods that rely on limited textbook materials are unable to meet the diverse needs of students. To solve the problems of insufficient coverage of multi-source corpora and limited adaptability of translation models, a corpus acquisition framework integrating knowledge discovery and domain discrimination was developed, and a translation model based on data fusion was designed. By using a web crawling system to capture bilingual discourse level corpora in new fields, and combining sentence segmentation strategies and dynamic programming to optimize alignment accuracy, high-quality parallel corpora
were generated. At the same time, a bidirectional encoder representation combined with WordPiece model was proposed to enhance sequence annotation performance by integrating part-of-speech and syntactic dependency features. The experiment outcomes showed that the proposed model had an accuracy of 0.92 and a processing time of only 12 seconds. For the translation, the proposed model had an accuracy close to 1.0 after 900 iterations, a false positive rate reduced to 0.05, and a translation time of 16 seconds, significantly better than traditional models. The results indicate that multi-source corpus acquisition and data fusion techniques can effectively enhance the processing capability of translation systems for complex contexts, providing high-precision solutions for interdisciplinary English translation.

Keywords: Multi-source information; Corpus; Data fusion; Bidirectional encoder; WordPiece

Cite As

W. Meng, L. Yu, Y. Zhu, "College English Translation Intelligent Systems Technology Based on Multi-Source
Information Corpus Acquisition and Data Fusion", Engineering Intelligent Systems, vol. 34 no. 1, pp. 109-118,
2026.

Downloads

Published

2026-01-01

Issue

Vol. 34 No. 1 (2026): International Journal of Engineering Intelligent Systems

Section

Article

License

The submission of a paper implies that, if accepted for publication, it will not be published elsewhere in the same form, in any language, without the prior consent of the publisher. Before publication, authors are requested to assign copyright to CRL Publishing Ltd. This allows CRL to sanction photocopying, and to authorize the reprinting of issues or volumes according to demand. Authors' traditional rights will not be jeopardized by assigning Copyright in this way, as they retain the right to reuse the material following publication, and to veto third-party publication.