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• W4308391738 abstract "Text in one language can be mechanically translated into another language using machine translation (MT). It is possible to anticipate a sequence of words, generally modeling full sentences using machine translation in a single integrated model. Human language's flexibility makes automatic translation an artificial intelligence (AI) challenge of the highest order. A single model rather than a pipeline of fine-tuned models is now the best way to attain state-of-the-art outcomes in machine translation. For example, words having numerous meanings, phrases that use more than one grammatical structure, and other grammar issues make it difficult for a machine to translate; however, many misinterpretations translate to be a breeze. A teacher's job is to assist pupils in overcoming the emotional and cognitive obstacles that stand in the way of developing effective problem-solving abilities. Students will benefit from developing problem-solving abilities since they will apply what they have learned to new circumstances. MT-AI, machine translation technology, and products have been employed in a wide range of applications, including business travel, tourism, and cross-lingual information retrieval. Text translation and phonetic translation are two types of translations that focus on the content of the source language. It is possible to create self-learning systems by injecting machine learning techniques into existing software and then observing the results of such injection. Computer software can translate a massive volume of text in a short period. It takes longer for a human translator to perform the same work as a computer program. The simulation investigation is developed based on correctness and effectiveness, demonstrating the proposed framework's reliability of 95.1%." @default.
• W4308391738 created "2022-11-11" @default.
• W4308391738 creator A5063631738 @default.
• W4308391738 date "2022-11-07" @default.
• W4308391738 modified "2023-10-17" @default.
• W4308391738 title "Study on Machine Translation Teaching Model Based on Translation Parallel Corpus and Exploitation for Multimedia Asian Information Processing" @default.
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• W4308391738 doi "https://doi.org/10.1145/3523282" @default.
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