Sigma-lognormal modeling of speech
C. Carmona-Duarte M. A. Ferrer R. Plamondon A. Gomez-Rodellar P. Gomez-Vilda
Human movement studies and analyses have been fundamental in many scientific
domains, ranging from neuroscience to education, pattern recognition to
robotics, health care to sports, and beyond. Previous speech motor models were
proposed to understand how speech movement is produced and how the resulting
speech varies when some parameters are changed. However, the inverse approach,
in which the muscular response parameters and the subject's age are derived
from real continuous speech, is not possible with such models. Instead, in the
handwriting field, the kinematic theory of rapid human movements and its
associated Sigma-lognormal model have been applied successfully to obtain the
muscular response parameters. This work presents a speech kinematics based
model that can be used to study, analyze, and reconstruct complex speech
kinematics in a simplified manner. A method based on the kinematic theory of
rapid human movements and its associated Sigma lognormal model are applied to
describe and to parameterize the asymptotic impulse response of the
neuromuscular networks involved in speech as a response to a neuromotor
command. The method used to carry out transformations from formants to a
movement observation is also presented. Experiments carried out with the
(English) VTR TIMIT database and the (German) Saarbrucken Voice Database,
including people of different ages, with and without laryngeal pathologies,
corroborate the link between the extracted parameters and aging, on the one
hand, and the proportion between the first and second formants required in
applying the kinematic theory of rapid human movements, on the other. The
results should drive innovative developments in the modeling and understanding
of speech kinematics.