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SIGPRO
2002
58views more  SIGPRO 2002»
13 years 4 months ago
A HMM approach to the estimation of random trajectories on manifolds
Dynamic image analysis requires the estimation of time-varying model parameters (e.g., shape coe cients). This can be11 seen as states of a dynamic model which are restricted to a...
Jorge S. Marques, João Miranda Lemos, Arnal...
NAACL
2003
13 years 6 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
ICASSP
2008
IEEE
13 years 11 months ago
Statistical approach to vocal tract transfer function estimation based on factor analyzed trajectory HMM
In this paper, we describe a novel statistical approach to the vocal tract transfer function (VTTF) estimation of a speech signal based on a factor analyzed trajectory hidden Mark...
Tomoki Toda, Keiichi Tokuda
IJCAI
2003
13 years 6 months ago
Where is ...? Learning and Utilizing Motion Patterns of Persons with Mobile Robots
Whenever people move through their environments they do not move randomly. Instead, they usually follow specific trajectories or motion patterns corresponding to their intentions....
Grzegorz Cielniak, Maren Bennewitz, Wolfram Burgar...
ICRA
2010
IEEE
142views Robotics» more  ICRA 2010»
13 years 3 months ago
Learning and planning high-dimensional physical trajectories via structured Lagrangians
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...
Paul Vernaza, Daniel D. Lee, Seung-Joon Yi