Speech Recognition Algorithm And Implementation

Generally speaking, speech recognition is a process, through which the speech signal is converted into text. It goes without saying that the research on speech recognition is of great significance, as it's one of the important research fields in pattern recognition and has lots of application. For example, it will facilitate human's interaction with the machines. Voice can be used as an input method, and it will save people's time and effort when they are inputting text on a computer. Besides, speech recognition can also be used to control some machines, like automobiles, airplanes or mobile phones.This thesis introduces some theories about speech recognition and also presents the results of some experiments of improving the speech recognition algorithms. In chapter 2 we describe the processing of the speech signal and the feature extraction. We mainly focus on two types of features and make comparison between them when we are carrying out the experiment of isolated-word speech recognition. And in the next chapter, we move on to the Hidden Markov Model and its application in speech recognition. After the basic introduction of this mathematic model, we try to use it in isolated-word speech recognition. And then we continue with the continuous speech recognition using hidden markov model. The structure of a continuous speech recognition system is introduced and we also discuss several topics like, how to select the speech unit, how to improve the parameters of the hidden markov model. A toolbox called HTK and a speech database TIMIT are introduced and then they are used to carry out the experiments of large vocabulary speaker-independent continuous speech recognition.