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Fuzziness is one of the essential characteristics of natural language. Fuzzy language is a language that expresses a fuzzy meaning; that is, a language with indefinite connotation and indefinite extension (Guo, 2021). Whether in literary and artistic works or people’s daily communication, the vagueness of words occupies an indispensable position, especially in the translation process of English literary and artistic works. There is a lot of ambiguity and polysemy in natural language, which makes it difficult for machine translation systems to accurately understand and translate texts. For example, the word bank can represent either an organization that provides various financial services (for example, keeping or lending money) or the side of a river. The specific meaning needs to be judged according to the context, which requires that the machine translation system can understand and deal with this ambiguity. The accuracy of translation affects the level of communication. High-quality translation originates from the analysis and understanding of semantics, and shaping high-precision translation methods has high application value (BENBADA & BENAOUDA, 2023). Traditional translation methods with grammatical type variables have drawbacks such as semantic ambiguity, inaccurate quantifiers, and low translation accuracy (Yin, 2023). In response to this drawback, this article proposes an accurate English language translation method based on semantic analysis to improve the accuracy of English language translation.
Ambiguity is one of the main characteristics of English words and literature. It is precisely because of this that English literature gives readers a wider imagination and reading space, which is also its charm (Garcés-Báez & López-López, 2017). However, when translating English words and literature, this linguistic ambiguity cannot be ignored. How to truly understand the ambiguity of English words and literature semantics to make accurate translations is an issue that needs serious consideration. If the vague semantics of English words and literature are ignored in the process of translation, it will inevitably hurt the artistic conception of literary works. However, meaning is highly dependent on the translation situation and requires an effective grasp of actual translation. This is an critical problem in the current English translation process. It is essential to deeply analyze the basic characteristics of English words and literature and propose effective translation strategies for fuzzy semantic translation. The traditional translation methods with grammatical type variables have the disadvantages of semantic ambiguity, inaccurate quantifiers, and low translation accuracy (Lin et al., 2017). Given these drawbacks, this paper proposes an artificial intelligence method based on semantic analysis for the accurate translation of vague meanings in English words and literature to improve the accuracy of English word translation.
The ultimate understanding of the English language is the understanding of semantics (Zhao, 2022). Although different languages have different characteristics and fuzziness, this greatly increases the translation practice. The fuzziness and accuracy of languages are mutually transformed to some extent, which makes translation possible. The fuzziness of language is not only the patent of literary works but is also reflected in various styles. Language fuzziness is mainly manifested in phonetics, grammar, semantics, and pragmatics.