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» Language model adaptation using Random Forests
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CCS
2006
ACM
13 years 11 months ago
Ring signatures without random oracles
Since the formalization of ring signature by Rivest, Shamir and Tauman in 2001, there are lots of variations appeared in the literature. Almost all of the variations rely on the ra...
Sherman S. M. Chow, Victor K.-W. Wei, Joseph K. Li...
LREC
2008
118views Education» more  LREC 2008»
13 years 9 months ago
Evaluation of several Maximum Likelihood Linear Regression Variants for Language Adaptation
Multilingual Automatic Speech Recognition (ASR) systems are of great interest in multilingual environments. We studied the case of the Comunitat Valenciana where the two official ...
Míriam Luján-Mares, Carlos D. Mart&i...
ICASSP
2011
IEEE
12 years 11 months ago
Relevance language modeling for speech recognition
Language models for speech recognition tend to be brittle across domains, since their performance is vulnerable to changes in the genre or topic of the text on which they are trai...
Kuan-Yu Chen, Berlin Chen
DKE
1998
87views more  DKE 1998»
13 years 7 months ago
Using Natural Language Sources in Model-Based Knowledge Acquisition
This paper introduces a well defined co-operation between domain expert, knowledge engineer, and knowledge acquisition and transformation tools. First, the domain expert supported...
Gabriele Schmidt, Thomas Wetter
CORR
2010
Springer
182views Education» more  CORR 2010»
13 years 7 months ago
SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization
The sequential parameter optimization (spot) package for R (R Development Core Team, 2008) is a toolbox for tuning and understanding simulation and optimization algorithms. Model-...
Thomas Bartz-Beielstein