The rapid development of artificial intelligence, natural language processing, and multilingual machine translation technologies has significantly increased the importance of parallel corpora in translation modeling and translation education. Modern intelligent translation systems increasingly rely on semantically adapted multilingual corpora for contextual interpretation, semantic image learning, and adaptive translation generation. This study examines the linguistic, semantic, technological, and pedagogical requirements for parallel corpora in teaching translation modeling in a multilingual computing environment.

parallel corpus, modeling, computational linguistics, machine translation, multilingual corpus, semantic matching, intelligent translation systems, NLP.

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