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» The Combining Classifier: To Train or Not to Train
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JMM2
2007
118views more  JMM2 2007»
13 years 8 months ago
Universal Detection of JPEG Steganography
Abstract— In this paper, we present a novel universal approach which consists in exploring statistics in the compressed frequency domain. This approach is motivated by two main c...
Johann Barbier, Eric Filiol, Kichenakoumar Mayoura
TSP
2008
89views more  TSP 2008»
13 years 8 months ago
The Kernel Least-Mean-Square Algorithm
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
Weifeng Liu, Puskal P. Pokharel, Jose C. Principe
CSL
2000
Springer
13 years 8 months ago
Efficient speech recognition using subvector quantization and discrete-mixture HMMS
This paper introduces a new form of observation distributions for hidden Markov models (HMMs), combining subvector quantization and mixtures of discrete distrib utions. Despite w...
Vassilios Digalakis, S. Tsakalidis, Costas Harizak...
JAIR
2000
131views more  JAIR 2000»
13 years 8 months ago
An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email
This paper describes a novel method by which a spoken dialogue system can learn to choose an optimal dialogue strategy from its experience interacting with human users. The method...
Marilyn A. Walker
CORR
1998
Springer
113views Education» more  CORR 1998»
13 years 8 months ago
Letter to Sound Rules for Accented Lexicon Compression
This paper presents trainable methods for generating letter to sound rules from a given lexicon for use in pronouncing out-ofvocabulary words and as a method for lexicon compressi...
V. Pagel, Kevin Lenzo, Alan W. Black