Design and Implementation of Foreign Language Recognition and Translation APP Based on Artificial Intelligence

Abstract

Globalization has created the demand for cross-language communication, which has promoted the development of machine translation applications (APPs) based on artificial intelligence (AI) for foreign language recognition and translation. The purpose of this study is to develop and implement a mobile application program that can accurately identify and translate foreign languages. APP adopts advanced artificial intelligence technology, uses optical character recognition (OCR) technology to identify the text in images, and uses neural network architecture based on transformer for machine translation. In the data preprocessing stage, text cleaning, word segmentation and other preprocessing steps are performed to create accurate translation input. A translation model is trained on a large bilingual mapping data set to learn the mapping knowledge relationship between the source language and the target language. After a series of tests and experiments, the application of foreign language identification and translation shows the high accuracy and speed of multilingual input and output. The accuracy of this application is 0.9, and the maximum delay is only 180 milliseconds. Although there is still room for improvement in the background of professional fields or complex scenes, this application is an effective tool for cross-language communication. Future work should focus on further optimizing translation models, improving the accuracy of translation for specific domain terms, and enhancing the personalized service capabilities of the APP.