Pre-processing of input features using LPC and warping process

This paper presents pre-processing of input features to artificial neural network (NN). This is for preparation of reliable reference templates for the set of words to be recognized. The first task is to extract pitch features using Pitch Scale Harmonic Filter (PSHF) algorithm. Another task is to align the input frames (test set) to the reference template (training set) using a modified DTW algorithm called DTW fixing frame (DTW-FF) algorithm. This proper time normalization is needed since NN is designed to compare data of the same length; same speech can varies in their duration. By performing frame fixing or time normalization, the test set and the training set is adjusted to a fix number of frames throughout the sets utilizing the local distance score of the matched features. Then those features can be adapted to NN for further recognition tuning.