Implementation of Voice Search Technology in Digital Library Systems

Abstract

Incorporating voice search features into digital libraries enhances user interaction and accessibility. Users with disabilities and many others often struggle with typing, making precise keyword entry, which digital libraries require, irritating and frustrating. This project focuses on hands-free walking technology using voice recognition optimized for easy interaction with digital libraries. With NLP and speech recognition, users can provide simple commands, and the system will use the databases to look up and retrieve pertinent information. The system interprets the intent behind queries spoken out loud, processes them, and returns relevant data stored in the digital library. Search operations become less burdensome, and users are able to multitask as complex automation eases effort on the user experience. Furthermore, voice searches need not be restricted to English, expanding access to digital resources. Additionally, the system employs algorithms based on machine learning to understand user preferences better, and automate tasks to enhance accuracy, providing users with tailored responses to queries. This paper discusses the architecture, implementation, and advantages of voice searching in digital libraries, considering background noises, accents, and privacy concerns. This proposed solution aims to foster the adaptability of digital libraries with contemporary technologies, enhancing usability and inclusivity.