Wednesday, July 19, 2017
Friday, October 30, 2015
Saturday, June 6, 2015
Sherif Mohamed Abdel Monem Engineering Ph.D. Dissertation Speech Analysis Synthesis Northeastern University
Sherif Mohamed Abdel Monem Ph.D. Dissertation Speech Analysis Synthesis Recognition
Synopsis
The research is about the study of the transmission line networks of the vocal tract with applications of speech analysis, synthesis and recognition. The output response is calculated for cascaded transmission line networks representing the vocal and nasal tracts. The reflection coefficients at various junctions of the transmission line network model correspond to the shape of the vocal tract at any particular time and mode of articulation. For lossless transmission line networks the analysis is presented in section IV-A1b, For lossy networks in section IV-A1b, and for networks with nonequal length segments in section IV-A1c.
In the course of these derivations a new analysis technique for transmission line network response is developed (Ch. IV). In contrast to the usual detailed analysis of the forward and backward waves using a section by section approach, the entire transmission line configuration is considered a system. The pursuit of this new analysis leads to the introduction of several analytical tools which facilitates the computation. Examples of these analytical tools are: (a) loop-gains (Sec. IV-B and App. Q), pseudo-loop gains (Sec. IV-B and App. R), subtree-pseudo-loop gains (Sec. IV-B and App. R), subtree-pseudo-loop gains (Sec. IV-B and App. M) and path gains (sec. IV-A2 and Sec. IV-B).
The synthesis of the transmission line networks is treated for various given parameters: (a) for input-output response (Sec. IV-Fa and Fb), (b) for a given characteristic equation polynomial (sec. IV-Eb). The recursive solution of the autocorrelation normal equations, as applied to the synthesis of transmission line network, is represented in Appendix M. A discussion of the use of an analog signal (i.e. a triangular pulse for the excitation of a transmission line network) in the analysis and synthesis of the transmission line model is explored in Sec. V-a.
As an illustration of the use of a transmission model in various speech applications and a discussion of the adaptability of the cascaded transmission line network for the simulation of non-nasalized speech sounds and transmission line T network for the simulation of nasalized speech sounds are represented in Sec. V-B.
The model
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http://faculty.kfupm.edu.sa/ee/sBaiyat/events/IEEETEM2001/s5p1.pdf
Synopsis
The research is about the study of the transmission line networks of the vocal tract with applications of speech analysis, synthesis and recognition. The output response is calculated for cascaded transmission line networks representing the vocal and nasal tracts. The reflection coefficients at various junctions of the transmission line network model correspond to the shape of the vocal tract at any particular time and mode of articulation. For lossless transmission line networks the analysis is presented in section IV-A1b, For lossy networks in section IV-A1b, and for networks with nonequal length segments in section IV-A1c.
In the course of these derivations a new analysis technique for transmission line network response is developed (Ch. IV). In contrast to the usual detailed analysis of the forward and backward waves using a section by section approach, the entire transmission line configuration is considered a system. The pursuit of this new analysis leads to the introduction of several analytical tools which facilitates the computation. Examples of these analytical tools are: (a) loop-gains (Sec. IV-B and App. Q), pseudo-loop gains (Sec. IV-B and App. R), subtree-pseudo-loop gains (Sec. IV-B and App. R), subtree-pseudo-loop gains (Sec. IV-B and App. M) and path gains (sec. IV-A2 and Sec. IV-B).
The synthesis of the transmission line networks is treated for various given parameters: (a) for input-output response (Sec. IV-Fa and Fb), (b) for a given characteristic equation polynomial (sec. IV-Eb). The recursive solution of the autocorrelation normal equations, as applied to the synthesis of transmission line network, is represented in Appendix M. A discussion of the use of an analog signal (i.e. a triangular pulse for the excitation of a transmission line network) in the analysis and synthesis of the transmission line model is explored in Sec. V-a.
As an illustration of the use of a transmission model in various speech applications and a discussion of the adaptability of the cascaded transmission line network for the simulation of non-nasalized speech sounds and transmission line T network for the simulation of nasalized speech sounds are represented in Sec. V-B.
The model
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I-INTRODUCTION
In many areas of engineering research, one deals with a system that is related to some physical process. One way to be able to study the performance of such system is through the examination of the physical phenomena involved. This can be achieved by finding a suitable model that best describes the system behavior, with reasonable and sufficient degree of simplicity and accuracy. Therefore, a search for such a model that satisfies these criteria seems of great importance.
Many physical phenomena, such the one involving signal propagation through multimedia, are found to have common features and modes of propagation. For such systems, a unified model seems appropriate and highly desirable.
Many physical phenomena, such the one involving signal propagation through multimedia, are found to have common features and modes of propagation. For such systems, a unified model seems appropriate and highly desirable.
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http://faculty.kfupm.edu.sa/ee/sBaiyat/events/IEEETEM2001/s5p1.pdf
A.Benkrid, «Real-time TLM Vocal Tract Modelling », PhD Thesis, University of Nottingham, 1989.
http://www.ntu.edu.sg/home/aseschng/SpeechTechWeb/members/xiaoxiong/XiaoXiongRevisedThesis05Oct09.pdf
Thursday, January 29, 2015
Saturday, January 3, 2015
Analysis of SAR Resolution using Phasors Approach
Results are presented from a study of azimuth resolution of a generic Synthetic Aperture Radar (SAR) under conditions of uncompensated motion errors.
in progress.
in progress.
Sunday, April 7, 2013
Tuesday, February 19, 2013
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