Title: English translation method based on natural language processing in IoT environment on research

Authors: Fei Wu

Addresses: School of Foreign Languages, Harbin University of Science and Technology, Harbin, 150000, China

Abstract: Long English sentences in machine translation become the main factor affecting the quality of machine translation with its characteristics of more words and complex sentence structure. In this paper, we propose a translation method incorporating syntactic features in the field of natural language processing to address the problem of poor translation quality of English long sentences in machine translation. The method combines the linguistic template-based translation method and the conditional random field-based statistical translation method to slice and process long sentences by syntactic dimension and statistical dimension, and then improve the quality of machine translation. The experimental results show that the BLEU score of long sentences of English corpus improves about 2.1% and the NIST score improves about 1.1% after the training of the model proposed in this paper, which proves that the translation method of this paper improves the translation quality of long sentences of English.

Keywords: machine translation; natural language processing; NLP; English long sentence translation; contextualisation; internet of things; IoT; automatic calibration system.

DOI: 10.1504/IJCISTUDIES.2024.144050

International Journal of Computational Intelligence Studies, 2024 Vol.13 No.1/2, pp.40 - 59

Received: 10 Apr 2023
Accepted: 15 Sep 2023
Published online: 22 Jan 2025 *

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