Applications of Speech Recognition: A Survey

Abstract

One important area of natural language processing (NLP) and artificial intelligence (AI) is speech recognition, which converts spoken language into text. Its evolution spans from early rule-based systems like Bell Labs’ “Audrey” to modern deep learning-based architectures, significantly improving accuracy and usability. Applications extend across healthcare, education, telecommunications, defence, robotics, and consumer electronics, enhancing accessibility and human–machine interaction. Despite advancements, challenges such as accent variability, noisy environments, and ethical issues persist. Current research emphasizes deep neural networks, clustering, and statistical models, with continuous progress driving speech recognition toward greater efficiency, inclusivity, and real-world adoption.