|Title||Hidden Dynamic Models for Speech Processing Applications|
|Year of Publication||2004|
|Authors||Lee, L. J.|
|Academic Department||Department of Electrical & Computer Engineering|
|University||University of Waterloo|
|City||Waterloo, Ontario, Canada|
|Thesis Type||Ph.D. Thesis|
Human speech has a dual nature: the goal of speech is to convey discrete linguistic symbols corresponding to the intended message while the actual speech signal is produced by the continuous and smooth movement of the articulators with rich temporal structures. Such a dual nature has been amazingly utilized by humans in a beneficial way but has presented a big challenge for both speech science and speech technology.
As a continuing effort to seek internal dynamics of human speech that can reflect the continuous shape change of the vocal tract and benefit the current speech technology, the second part of the thesis turns to a study of vocal-tract-resonance (VTR) dynamics, built upon the insights and experiences gained from studying articulatory dynamics. It verifies that VTR dynamics can be captured by simple dynamic equations, and a highly accurate and efficient piecewise linear mapping from VTR dynamics to the acoustic space is also carefully designed. Two novel VTR tracking methods are developed in this part: one is based on mimicking manual tracking of VTR dynamics by human experts and uses advanced image processing methods (active contours), the other is the natural outcome of formulating a HDM for VTR dynamics and recovering the hidden dynamics by Kalman smoothing.
Hidden Dynamic Models for Speech Processing Applications