Evaluation method for a voice recognition system modeled with discrete Markov chain

In this paper, we suggest an evaluation method for a voice recognition system modeled with discrete Markov chain. Our evaluations are mainly dependent on two characteristics of a system: 1) correctness of recognition for input data and 2) number of utterances. The main frame of the voice recognition system is composed of: 1) a voice input unit, 2) a voice recognition unit and 3) an output unit. Generally, a voice recognition system has its own list of words to recognize a word correctly. It means that the words which the system can recognize are restricted. A simple system can be expressed as a state transition diagram. Then we can make a transition probability matrix and calculate the state probability for each state. This means that we can evaluate the system numerically. Moreover we extend the simple model to the more general one and get numerical results to evaluate the two characteristics for the system.