Voice Recognition and Automatic Classification
Gerardo Mino‐Aguilar · 2015
In this work an Automatic Speech Recognition System is implemented, which makes use of an Automatic Pattern Recognition Processor that instead of working on Speech Recognition Techniques, it does so based on Artificial Vision paradigms, using images produced in function of intrinsic characteristics extracted from the speech for the Training Stages and Pattern Generation, thus using this information to classify appropriately this signals. Nevertheless, the State of the Technique in the area of Digital Signal Processing is used focused on the processing of the speech, which is very important for the generation of the signal conditioning algorithms, as well as the speech Feature Extraction. It was used and compared the performance of four different methods of Feature Extraction: Average Magnitude, Spectrograms (Time-Frequency), Linear Prediction Coefficients and finally we propose a technique called: Short time Analysis of the Fundamental Signal