Data-Driven Methods for Extracting Features from Speech

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" Data-Driven Methods for Extracting Features from Speech "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	148587
Doc. No	:	ET20379
Main Entry	:	Narendranat h Malayat h
Title Proper	:	Data-Driven Methods for Extracting Features from Speech
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Feature extraction plays a major role in any form of pattern recognition- Currentfeature extraction methods used for automatic speech recognition (ASR) and speakerverification rely mainly on properties of speech production (modeled by d-pole filters)and perception (critical band integration simulated by Mel/Bark filter bank). We proposestochastic methods t o design feature extraction methods which are trained t o alleviate theunwanted variability present in speech signal, In this dissertation we show that such data-driven met hods provide significant advantages over the conventional met hods for featureextraction..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL43506.pdf
Title and statement of responsibility and	:	Data-Driven Methods for Extracting Features from Speech [Thesis]