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Automatic Speech Recognition Using Lp-Dctc/Dcs Analysis Followed By Morphological Filtering, Penny Hix

Electrical & Computer Engineering Theses & Dissertations

Front-end feature extraction techniques have long been a critical component in Automatic Speech Recognition (ASR). Nonlinear filtering techniques are becoming increasingly important in this application, and are often better than linear filters at removing noise without distorting speech features. However, design and analysis of nonlinear filters are more difficult than for linear filters. Mathematical morphology, which creates filters based on shape and size characteristics, is a design structure for nonlinear filters. These filters are limited to minimum and maximum operations that introduce a deterministic bias into filtered signals.

This work develops filtering structures based on a mathematical morphology that utilizes …