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FTSIG
2007
136views more  FTSIG 2007»
13 years 8 months ago
The Application of Hidden Markov Models in Speech Recognition
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabula...
Mark J. F. Gales, Steve Young
FCCM
2002
IEEE
114views VLSI» more  FCCM 2002»
14 years 1 months ago
Implementing a Simple Continuous Speech Recognition System on an FPGA
Speech recognition is a computationally demanding task, particularly the stage which uses Viterbi decoding for converting pre-processed speech data into words or sub-word units. W...
Stephen J. Melnikoff, Steven F. Quigley, Martin J....
ICML
2009
IEEE
14 years 9 months ago
Large margin training for hidden Markov models with partially observed states
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
Thierry Artières, Trinh Minh Tri Do
CORR
2012
Springer
210views Education» more  CORR 2012»
12 years 4 months ago
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Vinayak Rao, Yee Whye Teh
TSP
2008
180views more  TSP 2008»
13 years 8 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein