Date of Award
12-2003
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Engineering
Department
Electrical Engineering
Major Professor
Charalmpidis, Dimitrios
Second Advisor
Ma, Jing
Third Advisor
Jilkov, Vesselin
Abstract
This thesis introduces a novel method for accurate pitch detection and speech segmentation, named Multi-feature, Autocorrelation (ACR) and Wavelet Technique (MAWT). MAWT uses feature extraction, and ACR applied on Linear Predictive Coding (LPC) residuals, with a wavelet-based refinement step. MAWT opens the way for a unique approach to modeling: although speech is divided into segments, the success of voicing decisions is not crucial. Experiments demonstrate the superiority of MAWT in pitch period detection accuracy over existing methods, and illustrate its advantages for speech segmentation. These advantages are more pronounced for gain-varying and transitional speech, and under noisy conditions.
Recommended Citation
Kura, Vijay, "Novel Pitch Detection Algorithm With Application to Speech Coding" (2003). University of New Orleans Theses and Dissertations. 52.
https://scholarworks.uno.edu/td/52
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.