This work investigates the application of Automatic Speech Recognition (ASR) within embedded systems, focusing on practical implementation and theoretical underpinnings. The author, an experienced educator in electronics and communication engineering, details the use of the Hidden Markov Model (HMM) for speech signal processing and introduces a codebook refining algorithm to analyze diverse human voices. The book aims to enhance student comprehension of ASR principles and their integration into hardware, drawing upon the author's pedagogical background to present the material effectively.

The author, drawing on extensive teaching experience in electronics and communication engineering, presents this book as a resource to enrich students' knowledge of Automatic Speech Recognition (ASR) in embedded systems. The inclusion of problem-solving techniques for Hidden Markov Models and a codebook refining algorithm suggests a practical, hands-on approach. The author strongly recommends the book for engineering students and researchers, indicating an intended audience seeking to deepen their understanding of ASR principles and applications.