Integration of Transformer Model Text Summarization and Text-to-Speech in Helping Document Understanding in the Bukudio Application

Abstract

The need for effective, accurate and precise understanding of information will provide optimization of the decision-making process, increase knowledge and quality of life. Understanding information in relation to the document summarization process, if done manually, sometimes takes quite a long time. Text summarization techniques which are useful as document summarizers have been developed and applied to various things such as summarizing important documents, news texts or customer feedback. In this article, text summarization using the text rank method and transformer modeling integrated with text to speech techniques is developed in the Bukudio application, which is an application that provides audio versions of book documents in the application database. Based on the test results, the evaluation process was carried out using the Rouge method and gave the best results in calculating the Rouge 1 overlap monogram resulting in 0.523 for the F1 Score value, 0.434 for the precision value and 0.659 for the recall value. This research will be developed using other methods so that not only files in PDF document format can be processed, but other EPUB (Electronic Publication) files.