Author(s)

Yan Huang ¹, Xiaoli Cheng ¹

Affiliation(s)

¹ Gongqing College of Nanchang University, Jiujiang, Jiangxi, China

Corresponding Author

Yan Huang

ABSTRACT

Machine translation technology has made great progress in the past few decades, especially the proposal of statistical machine translation technology. If the meaning of the translation can be roughly understood in a limited field of some specific languages, it can be said that it has not reached the level of correctly expressing the meaning of the original text in all fields of all languages. Computer assisted translation technology has been widely developed as a viable alternative to machine translation. Interactive machine translation technology is one of the feasible models. In order to verify the feasibility of computer-aided translation in foreign language translation, this technology has been widelyused. Optimization algorithm based on human-computer interaction, this paper tests the translation accuracy and speed of computer-aided foreign language translation and traditional translation under different sentences (words, phrases, sentences, paragraphs). The test results show that the translation accuracy of computer-aided foreign language translation optimization algorithm based on human-computer interaction is higher than that of traditional translation under words, phrases, sentences and paragraphs, and the translation accuracy is more than 96%, while the highest accuracy of traditional translation is only 94.38%; In terms of translation speed, human-computer interaction translation is still faster, reaching 4.41 sentences / second. It fully proves the superiority and feasibility of the translation optimization algorithm proposed in this paper.

KEYWORDS

Human Computer Interaction, Computer Aided, Foreign Language Translation, Optimization Algorithm

CITE THIS PAPER

Yan Huang, Xiaoli Cheng, Computer Aided Foreign Language Translation Optimization Algorithm Based on Human-computer Interaction. Automation and Machine Learning (2023) Vol. 4: 1-6. DOI: http://dx.doi.org/10.23977/autml.2023.040201.

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