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» Selectivity Estimation using Probabilistic Models
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ICASSP
2009
IEEE
15 years 11 months ago
Using collective information in semi-supervised learning for speech recognition
Training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. In this paper, we describe a novel semi-supervised learn...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
NIPS
2001
15 years 6 months ago
Sequential Noise Compensation by Sequential Monte Carlo Method
We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...
K. Yao, S. Nakamura
IJNSEC
2007
144views more  IJNSEC 2007»
15 years 4 months ago
IPLess Stochastic Anonymous Routing Algorithm Using Multi-Agent Systems
The ability of communicating with a selected party anonymously is an important aspect of network security. Communicating anonymously means that no adversary can discern who is com...
Magdy Saeb, Meer Hamza, Ahmed El-Shikh
WSC
2001
15 years 6 months ago
Analysis of simulation experiments by bootstrap resampling
This tutorial considers some very general procedures for analysing the results of a simulation experiment using bootstrap resampling. Bootstrapping has come to be recognised in st...
Russell C. H. Cheng
CVIU
2006
162views more  CVIU 2006»
15 years 4 months ago
Unsupervised scene analysis: A hidden Markov model approach
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...
Manuele Bicego, Marco Cristani, Vittorio Murino