Abstract 3 Overview of the Characteristics of Automatic Speech Recognition Systems 4 Number of Words 4 Use of Grammar 5 Discrete Speech 5Speaker Dependency 6Early Approaches to Automatic Speech Recognition 6Acoustic-Phonetic Approach 7Statistical Pattern Recognition Approach 8Modern Approach to Automatic Speech Recognition 8Hidden Markov Models 9 Training of an Automatic Speech Recognition System Based on HMMs 11 Sub-Word Units 11 Applications of Automatic Speech Recognition Systems 12Automated Call-Type Recognition 13Data Entry 13Future Applications Using Automatic Speech Recognition Systems 14 Conclusion 14 References 15AbstractWith the advances of technology, a lot of people may think that integrating the ability of understanding human speech in a computer system is a piece of cake. However, scientists disagree. Since the early nineteen fifties, scientists have tried to implement the perfect automatic speech recognition system, but they failed. They were successful in making the computer recognise a large number of words, but till now, a computer that understands everything without meeting any conditions does not exist. Due to the enormous applications, a lot of money and time is spent in improving speech recognition systems. SPEECH RECOGNITION: PRINCIPLES AND APPLICATIONSNowadays, computer systems play a major role in our lives. They are used everywhere beginning with homes, offices, restaurants, gas stations, and so on. Nonetheless, for some, computers still represent the machine they will never know how to use. Communicating with a computer is done using a keyboard or a mouse, devices many people are not comfortable using. Speech recognition solves this problem and destroys the boundaries between humans and computers. Using a computer will be as easy as talking with your friend. Unfortunatel...
