The first stage of any recogniser development project is data preparation. Speech data is needed both for training and for testing. In the system to be built here, all of this speech will be recorded from scratch and to do this scripts are needed to prompt for each sentence. In the case of the test data, these prompt scripts will also provide the reference transcriptions against which the recogniser's performance can be measured and a convenient way to create them is to use the task grammar as a random generator. In the case of the training data, the prompt scripts will be used in conjunction with a pronunciation dictionary to provide the initial phone level transcriptions needed to start the HMM training process. Since the application requires that arbitrary names can be added to the recogniser, training data with good phonetic balance and coverage is needed. Here for convenience the prompt scripts needed for training are taken from the TIMIT acoustic-phonetic database.
It follows from the above that before the data can be recorded, a phone set must be defined, a dictionary must be constructed to cover both training and testing and a task grammar must be defined.