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Fuzzy information recognition and translation processing in English interpretation based on a generalized maximum

Li Yin1

  • 1Chengdu Gingko College of Hospitality Management, Chengdu, Sichuan, China.

Peerj. Computer Science
|March 4, 2024
PubMed
Summary

This study introduces a generalized maximum likelihood ratio (GLR) algorithm to identify and process fuzzy information in English interpretation. The method enhances translation accuracy and fluency by reducing ambiguity in cross-language communication.

Keywords:
Fuzzy languageGeneralized maximum likelihood ratioIntelligent identificationOral interpretation

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Area of Science:

  • Computational Linguistics
  • Natural Language Processing
  • Communication Studies

Background:

  • Cross-language communication relies heavily on English interpretation.
  • Ambiguous information (vocabulary, syntax) in interpretation leads to inaccuracies and fluency issues.

Purpose of the Study:

  • To propose a method for identifying and processing fuzzy information in English interpretation.
  • To improve the quality and efficiency of interpretation performance.

Main Methods:

  • Systematic analysis of fuzzy information types in interpretation.
  • Application of the generalized maximum likelihood ratio (GLR) algorithm for uncertainty.
  • Development of a fuzzy information recognition model trained on a large interpretation corpus.
  • Implementation of contextual inference and adaptation strategies for translation processing.

Main Results:

  • The proposed GLR-based method effectively identifies fuzzy information in interpretation.
  • Experimental results demonstrate significant improvements in interpretation quality and fluency.
  • The method successfully reduces ambiguity stemming from fuzzy information across various scenarios.

Conclusions:

  • The generalized maximum likelihood ratio algorithm provides a robust framework for handling fuzzy information in English interpretation.
  • This approach enhances the accuracy and naturalness of interpreted content.
  • The method offers a valuable tool for improving real-world interpretation services.