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| Document Type
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Latin Dissertation
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| Language of Document
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English
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| Record Number
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148587
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| Doc. No
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ET20379
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| Main Entry
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Narendranat h Malayat h
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| Title Proper
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Data-Driven Methods for Extracting Features from Speech
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| Note
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This document is digital این مدرک بصورت الکترونیکی می باشد
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| Abstract
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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..
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| Subject
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Electericl tess
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برق
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| electronic file name
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TL43506.pdf
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| Title and statement of responsibility and
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Data-Driven Methods for Extracting Features from Speech [Thesis]
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http://lib.khuisf.ac.ir/site/catalogue/148587
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