A Novel User Interface for Text Dependent Human Voice Recognition System
Keywords:Additive Prognostication (AP), band-pass filtering, feature extraction, human voice, recognition rate, Wavelet decomposition/reconstruction tree.
In an effort to provide a more efficient representation of the speech signal, the application of the wavelet analysis is considered. This research presents an effective and robust method for extracting features for speech processing. Here, we proposed a novel user interface for Text Dependent Human Voice Recognition (TD-HVR) system. The proposed HVR model utilizes decimated bi-orthogonal wavelet transform (DBT) approach to extract the low level features from the given input voice signal, then the noise elimination will be done by band pass filtering followed by normalization for better quality of a voice signal and finally the formants of a train and test voices will be calculated by using the Additive Prognostication (AP) algorithm. Simulation results have been compared with the existing HVR schemes, and shown that the proposed user interface system has performed superior to the conventional HVR systems with an accuracy rate of approximately 99 %.
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