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ICASSP
2011
IEEE
14 years 11 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
IJON
2002
120views more  IJON 2002»
15 years 7 months ago
The recognition and analysis of animate objects using neural networks and active contour models
: In this paper we describe a method for tracking walking humans in the visual field. Active contour models are used to track moving objects in a sequence of images. The resulting ...
Ken Tabb, Neil Davey, Rod Adams, Stella J. George
BMVC
2010
15 years 5 months ago
Discriminative Topics Modelling for Action Feature Selection and Recognition
This paper presents a framework for recognising realistic human actions captured from unconstrained environments. The novelties of this work lie in three aspects. First, we propos...
Matteo Bregonzio, Jian Li, Shaogang Gong, Tao Xian...
INTERSPEECH
2010
15 years 2 months ago
Bayesian speaker recognition using Gaussian mixture model and laplace approximation
This paper presents a Bayesian approach for Gaussian mixture model (GMM)-based speaker identification. Some approaches evaluate the speaker score of a test speech utterance using ...
Shih-Sian Cheng, I-Fan Chen, Hsin-Min Wang
BVAI
2005
Springer
16 years 1 months ago
A Neural Model of Human Object Recognition Development
The human capability of recognizing objects visually is here held to be a function emerging as result of interactions between epigenetic influences and basic neural plasticity mec...
Rosaria Grazia Domenella, Alessio Plebe