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An Automated English Translation Judging System Based on Feature Extraction Algorithm

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DOI: 10.23977/jaip.2022.050407 | Downloads: 14 | Views: 669

Author(s)

Ruichao Li 1

Affiliation(s)

1 School of Translation Studies, Xi'an Fanyi University, Xi'an, Shaanxi, China

Corresponding Author

Ruichao Li

ABSTRACT

As an important and necessary element in the assessment of students’ English language ability, translation is a comprehensive indicator of students’ mastery and ability to use English vocabulary, sentence structure, grammar, and other indicators. Compared to other types of questions, the task of marking translation is more demanding and time-consuming, and the objectivity and fairness of marking are more difficult to ensure because the assessment criteria for translation are relatively flexible. Feature extraction algorithms, which have developed rapidly and been widely used in recent years, can learn and extract development patterns from information such as images and texts, and make judgments in the corresponding context, while English translation(ET) texts have the characteristics of diverse and quantifiable feature points related to grading, and the feasibility of automatic grading exists. Therefore, this paper carries out the design and implementation of a relevant automatic RATING system based on feature extraction algorithms, with a view to improving the fairness, accuracy and efficiency of translation rating.

KEYWORDS

Feature Extraction Algorithm, English Translation, Automatic Trading, and Evaluation Criteria

CITE THIS PAPER

Ruichao Li, An Automated English Translation Judging System Based on Feature Extraction Algorithm. Journal of Artificial Intelligence Practice (2022) Vol. 5: 48-54. DOI: http://dx.doi.org/10.23977/jaip.2022.050407.

REFERENCES

[1] Rajitha Jasmine Rajappan, Thyagharajan Kondampatti Kandaswamy. (2022) A Composite Framework of Deep Multiple View Human Joints Feature Extraction and Selection Strategy with Hybrid Adaptive Sunflower Optimization-whale Optimization Algorithm for Human action Recognition in Video Sequences. Comput. Intell, 2, 366-396.
[2] Asma Naseer, Sarmad Hussain, Kashif Zafar, Ayesha Khan. (2022) A Novel Normal to Tangent Line (NTL) Algorithm for Scale Invariant Feature Extraction for Urdu OCR. Int. J. Document Anal. Recognit,1, 51-66.
[3] Lata Jaywant Sankpal, Suhas Haribhau Patil; Squiride Rank. (2022) Squirrel Ride Rank Algorithm-based Feature Extraction for Re-ranking of Web Pages. Int. J. Web Portals, 1, 1-23.
[4] Hassan Habib, Rashid Amin, Bilal Ahmed, Abdul Hannan. (2022) Hybrid Algorithms for Brain Tumor Segmentation, Classification and Feature Extraction. J. Ambient Intell. Humaniz. Comput, 5, 2763-2784.
[5] Najme Mansour, Gholam Reza Khayati, Behnam Mohammad Hasani Zade, SeyedMohammad Javad Khorasani, Roya Kafi Hernashki.(2022) A New Feature Extraction Technique Based on Improved Owl Search Algorithm: a Case Study in Copper Electrorefining Plant. Neural Comput. Appl, 10, 7749-7814.
[6] Kumod Kumar Gupta, Ritu Vijay, Pallavi Pahadiya, Shivani Saxena. (2022) Use of novel Thermography Features of Extraction and Different Artificial Neural Network Algorithms in Breast Cancer Screening. Wirel. Pers. Commun, 1,495-524.
[7] Nadezhda S. Lagutina, Ksenia V. Lagutina, Elena 1. Boychuk, Inna A. Vorontsova, llya V. Paramonov. (2020) Automated Rhythmic Device Search in Literary Texts Applied to Comparing Original and Translated Texts as Exemplified by English to Russian Translations, Autom. Control. Comput. Sci, 7,697-711.
[8] Alexander Zabolotskikh, Anna Zabolotskikh, Tatiana Dugina, Daria Tavberidze. (2021) Creating Individual Learning Paths in the Moodle Plugin for Undergraduate Students to Study English Grammar. Educ. Inf. Technol, 1,617-637.
[9] Ivana Simonova. (2019) Blended Approach to Learning and Practising English Grammar with Technical and Foreign Language University Students: Comparative Study. J. Comput. High, Educ, 2, 249-272.
[10] Ummadi Reddy, B. Venkata Ramana Reddy, B. Eswara Reddy. (2021) LESH- Feature Extraction and Cognitive Machine Learning Techniques for Recognitionof Lung Cancer Cells. Int. J. Comput, Aided Eng, Technol, 1, 32-45.
[11] P. Ajitha, A. Sivasangari, R. Immanuel Rajkumar, S. Poonguzhali. (2021) Design of Text Sentiment Analysis Tool Using Feature Extraction Based on Fusing Machine Learning Algorithms. J. Intell. Fuzzy Syst, 4, 6375-6383.
[12] Bhawna Ahuja, Virendra P. Vishwakarma. (2021) Deterministic Multikernel Extreme Learning Machine with Fuzzy Feature Extraction for Pattern Classification, Multim, Tools Appl, 21, 32423-32447.

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