Browsing Theses (MU) by Thesis Advisor "Zhao, Yunxin"
Now showing items 1-7 of 7
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Ensemble methods in large vocabulary continuous speech recognition
(University of Missouri--Columbia, 2008)Combining a group of classifiers and therefore improving the overall classification performance is a young and promising direction in Large Vocabulary Continuous Speech Recognition (LVCSR). Previous works on acoustic ... -
An exploration of composite language modeling for speech recognition
(University of Missouri--Columbia, 2013)Language models are one of the most critical knowledge sources of automatic speech recognition (ASR) systems. In the past decades, many language models have been developed, and some have proved useful and successful in ... -
A flexible speech feature converter based on an enhanced architecture of U-net
(University of Missouri--Columbia, 2020)In order to analyze speech or audio, many methods are applied to transform the time domain signals into various features such as the mel spectral features and WORLD vocoder features. These two types of features can both ... -
Language modeling for automatic speech recognition in telehealth
(University of Missouri--Columbia, 2005)Standard statistic n-gram language models play a critical and indispensable role in automatic speech recognition (ASR) applications. Though helpful to ASR, it suffers from a practical problem when lacking sufficient in-domain ... -
Modeling of the acoustic signal of an electric guitar amplifier using recurrent neural networks
(University of Missouri--Columbia, 2021)Neural networks have topped performance measures across a wide variety of computational tasks. These performances are prevalent within the domain of human perception type tasks such as classification or generation of images, ... -
Selecting data for multilingual multi-domain neural machine translation on low resource languages
(University of Missouri--Columbia, 2020)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] While machine translation has achieved impressive results on the world's most widely spoken languages, thousands of languages do not have the quantity ... -
Towards deep learning on speech recognition for Khmer language
(University of Missouri--Columbia, 2016)In order to perform speech recognition well, a huge amount of transcribed speech and textual data in the target language must be available for system training. The high demand for language resources constrains the development ...