Interpretation is an oral expression that converts the information heard and understood in the source language into the target language quickly and accurately, thus completing the role of information transmission. However, language contains too much fuzzy information, so it is inevitable to have fuzzy information in interpretation. The characteristics of fuzzy information, the differences between different languages and cultural backgrounds, and the unpredictability of interpretation have brought great challenges to interpretation. This paper proposes an improved generalized maximum likelihood ratio algorithm (GLR) for fuzzy information processing in English. To improve interpretation accuracy, this study analyzes the characteristics of language databases, vocabulary, grammar, and translation. More specifically, the principle of natural language processing research via intelligent recognition technology is introduced in this study. Secondly, the author introduces the role of vague language in oral communication. Then, this paper introduces the fuzzy language processing method via the improved GLR method in detail. Finally, the experimental results are given to verify the effectiveness of the method.
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Yin Li (2023) studied this question.
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