| Autor: |
He Hengheng |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Journal of Intelligent Systems, Vol 32, Iss 1, Pp 2385-95 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2191-026X |
| DOI: |
10.1515/jisys-2022-0257 |
| Popis: |
Translation of long sentences in English is a complex problem in machine translation. This work briefly introduced the basic framework of intelligent machine translation algorithm and improved the long short-term memory (LSTM)-based intelligent machine translation algorithm by introducing the long sentence segmentation module and reordering module. Simulation experiments were conducted using the public corpus and the local corpus containing self-collected linguistic data. The improved algorithm was compared with machine translation algorithms based on a recurrent neural network and LSTM. The results suggested that the LSTM-based machine translation algorithm added with the long sentence segmentation module and reordering module effectively segmented long sentences and translated long English sentences more accurately, and the translation was more grammatically correct. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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