A customized interactive multi-language learning application model using python

This paper aims to build a customized application for multiple language learning. There are various paid platforms and free platforms are available for language learning, however, the user has not given enough customization. Different application programming interfaces namely, speech-to-text, text translation, and text-to-speech are integratedwith multiple options for language selection. To demonstrate and evaluate this customized application, five languages are chosen to execute whereby the accuracy of the outcome can be scrutinized. The outcome is evaluated with native speakers concerning the exactness between the translated text and the translated audio. BLEU (Bilingual Evaluation Understudy) score is done for accessing the accuracy of translation and the Wilcoxon rank test is performed to find out the observed outcome is meeting the expected outcome. The results show that there is a significant difference between expected and observed outcomes for translation accuracy. The architecture of building a customized is discussed in this paper, which enables the user to build their learning app in python.Many real-time scenarios faced by people where a foreign language is required can be solved by this customized application.