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Full-Text Articles in Computer Engineering
Development Of Kinematic Templates For Automatic Pronunciation Assessment Using Acoustic-To-Articulatory Inversion, Deriq K. Jones
Development Of Kinematic Templates For Automatic Pronunciation Assessment Using Acoustic-To-Articulatory Inversion, Deriq K. Jones
Master's Theses (2009 -)
Computer-aided pronunciation training (CAPT) is a subcategory of computer-aided language learning (CALL) that deals with the correction of mispronunciation during language learning. For a CAPT system to be effective, it must provide useful and informative feedback that is comprehensive, qualitative, quantitative, and corrective. While the majority of modern systems address the first 3 aspects of feedback, most of these systems do not provide corrective feedback. As part of the National Science Foundation (NSF) funded study “RI: Small: Speaker Independent Acoustic-Articulator Inversion for Pronunciation Assessment”, the Marquette Speech and Swallowing Lab and Marquette Speech and Signal Processing Lab are conducting a …
Deep Neural Networks As Time Series Forecasters Of Energy Demand, Gregory Merkel
Deep Neural Networks As Time Series Forecasters Of Energy Demand, Gregory Merkel
Master's Theses (2009 -)
Short-term load forecasting is important for the day-to-day operation of natural gas utilities. Traditionally, short-term load forecasting of natural gas is done using linear regression, autoregressive integrated moving average models, and artificial neural networks. Many purchasing and operating decisions are made using these forecasts, and there can be high cost to both natural gas utilities and their customers if the short-term load forecast is inaccurate. Therefore, the GasDay lab continues to explore new ways to make better forecasts. Recently, deep neural networks (DNNs) have emerged as a powerful tool in machine learning problems. DNNs have been shown to greatly outperform …
Network-On-Chip Based H.264 Video Decoder On A Field Programmable Gate Array, Ian Barge
Network-On-Chip Based H.264 Video Decoder On A Field Programmable Gate Array, Ian Barge
Master's Theses (2009 -)
This thesis develops the first fully network-on-chip (NoC) based h.264 video decoder implemented in real hardware on a field programmable gate array (FPGA). This thesis starts with an overview of the h.264 video coding standard and an introduction to the NoC communication paradigm. Following this, a series of processing elements (PEs) are developed which implement the component algorithms making up the h.264 video decoder. These PEs, described primarily in VHDL with some Verilog and C, are then mapped to an NoC which is generated using the CONNECT NoC generation tool. To demonstrate the scalability of the proposed NoC based design, …