Voice Assisted Text Summarizer Using NLP

Abstract

A voice assisted text summarizer is a system that uses natural language processing (NLP) techniques to summarize long text documents into shorter, more concise versions that can be easily understood by users. The system can be activated by voice commands and is designed to facilitate the process of summarization, which is a time-consuming task for humans. The system employs various NLP techniques, such as sentence segmentation, word frequency analysis, and entity recognition, to identify the most relevant information in the text and generate a summary that captures the main points of the document. The system also uses machine learning algorithms to improve the quality of the summaries over time, as it learns from user feedback. The voice assistant functionality allows users to interact with the system hands-free, making it especially useful for people with visual impairments or those who are multitasking. Overall, a voice assisted text summarizer using NLP has the potential to improve productivity and make information more accessible to a wider audience. Text summaries can now be made in a variety of ways, but audio summaries still need to be created. The summaries' audio versions can be listened to in order to understand the content. The necessary information can be heard while people are working on other tasks. Voice-assisted text summary generators are useful because they provide condensed versions that may be read and heard in a short amount of time for people who frequently lack the time to read lengthy books or listen to longer audios.