Accuracy Correction of English Translation Based on Fuzzy Clustering Algorithm

As an international mainstream language, English is an important means in the process of international cultural interaction. Therefore, in recent years, countries have increased the training of English translation talents. The cultural differences objectively existing between different language systems have a great impact on the accuracy of translation. Translation does not simply transform one language into another, which involves deeper cultural exchanges. People expect to improve the accuracy of English translation, which correspondingly challenges English translators. Therefore, it is of practical and guiding significance to further study the improvement of English translation accuracy. In order to achieve the clustering and integration of English translation index parameters, this paper designs an English translation intelligent recognition algorithm based on FCM (Fuzzy Clustering Algorithm), corrects the English Chinese structural ambiguity in the part of speech recognition results according to the syntactic function of the parsing linear table, and finally obtains the recognition content. From the comprehensive evaluation results, the recognition accuracy based on FCM is 90.62%. This proves that this method has better information fusion analysis ability and improves the accuracy of translation.