Voice interface for the computerized registration system - De Ausen, Larissa Leen M. (2000)
In the past few years, the field of speech recognition technology has been completely revolutionized. Continuous speech recognition, which allows the user to dictate by speaking at a normal rate of speech leads the way for speech recognition to become a mainstream software item. A great advantage of speech recognition software is the speed and ease at which the user can input data. The application may provide an alternative tool to conventional user input such as the use of the keyboard and the mouse. This research presents a framework for a system that enlists a student in the course he or she wishes to take for a certain semester. Various types of speech recognition approaches are available, depending on the application involved. For the application intended, the best approach will be a limited vocabulary, isolated word recognition. For the enlistment process, it involves less than 200 different words, including spoken digits and letters, which are frequently used in the course numbers and sections. The entire speech recognition is implemented through the continuous density Hidden Markov Models (HMM). For limited vocabulary applications, such as this project, each HMM serves as a template for each word in the vocabulary. For speech recognition, each word is compared to each HMM. The HMM with the closest match will be the recognized word; otherwise, if no close match is found, the word spoken is assumed to be not part of the known vocabulary.