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Volume 13
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10.3390/app132312905
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Article

Neural Machine Translation Research on Syntactic Information Fusion Based on the Field of Electrical Engineering

by
Yanna Sang
1,2,
Yuan Chen
3 and
Juwei Zhang
1,2,*
1
School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China
2
Henan Province New Energy Vehicle Power Electronics and Power Transmission Engineering Research Center, Luoyang 471023, China
3
School of Foreign Languages, Henan University of Science and Technology, Luoyang 471023, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(23), 12905; https://doi.org/10.3390/app132312905
Submission received: 10 October 2023 / Revised: 6 November 2023 / Accepted: 30 November 2023 / Published: 1 December 2023
(This article belongs to the Special Issue Natural Language Processing (NLP) and Applications)
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Abstract

Neural machine translation has achieved good translation results, but needs further improvement in low-resource and domain-specific translation. To this end, the paper proposed to incorporate source language syntactic information into neural machine translation models. Two novel approaches, namely Contrastive Language–Image Pre-training(CLIP) and Cross-attention Fusion (CAF), were compared to a base transformer model on EN–ZH and ZH–EN pair machine translation focusing on the electrical engineering domain. In addition, an ablation study on the effect of both proposed methods was presented. Among them, the CLIP pre-training method improved significantly compared with the baseline system, and the BLEU values in the EN–ZH and ZH–EN tasks increased by 3.37 and 3.18 percentage points, respectively.
Keywords: neural machine translation; graph neural network; syntax parsing tree; transformer neural machine translation; graph neural network; syntax parsing tree; transformer

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MDPI and ACS Style

Sang, Y.; Chen, Y.; Zhang, J. Neural Machine Translation Research on Syntactic Information Fusion Based on the Field of Electrical Engineering. Appl. Sci. 2023, 13, 12905. https://doi.org/10.3390/app132312905

AMA Style

Sang Y, Chen Y, Zhang J. Neural Machine Translation Research on Syntactic Information Fusion Based on the Field of Electrical Engineering. Applied Sciences. 2023; 13(23):12905. https://doi.org/10.3390/app132312905

Chicago/Turabian Style

Sang, Yanna, Yuan Chen, and Juwei Zhang. 2023. "Neural Machine Translation Research on Syntactic Information Fusion Based on the Field of Electrical Engineering" Applied Sciences 13, no. 23: 12905. https://doi.org/10.3390/app132312905

APA Style

Sang, Y., Chen, Y., & Zhang, J. (2023). Neural Machine Translation Research on Syntactic Information Fusion Based on the Field of Electrical Engineering. Applied Sciences, 13(23), 12905. https://doi.org/10.3390/app132312905

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