Transcription, Translation and Summarization to Improve Educational Understanding

In-depth research on improving educational comprehension with the use of summarization, translation, and transcription technology is presented in this work. With an emphasis on accuracy and efficiency, a comparative analysis of the different models employed in these processes is carried out. In particular, we investigate the use of Whisper AI for transcription tasks and a Python interface for text summarization when implementing BART (Bidirectional and Auto-Regressive Transformers). Our results show that Whisper AI greatly increases transcription speed and accuracy, whereas BART excels at producing clear and succinct summaries. Better educational content distribution can be enabled by incorporating these modern techniques, which will make the material easier for teachers and students to understand. This research has many kinds of practical applications, from translating instructional materials between languages to producing succinct summarized notes and then providing flashcards and quizzes based on that.