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» Learning Models for Predicting Recognition Performance
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110
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NLE
2008
140views more  NLE 2008»
15 years 2 months ago
Active learning and logarithmic opinion pools for HPSG parse selection
For complex tasks such as parse selection, the creation of labelled training sets can be extremely costly. Resource-efficient schemes for creating informative labelled material mu...
Jason Baldridge, Miles Osborne
ML
2002
ACM
163views Machine Learning» more  ML 2002»
15 years 2 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
EMNLP
2007
15 years 4 months ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki
121
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Classifying laughter and speech using audio-visual feature prediction
In this study, a system that discriminates laughter from speech by modelling the relationship between audio and visual features is presented. The underlying assumption is that thi...
Stavros Petridis, Ali Asghar, Maja Pantic
ICASSP
2010
IEEE
15 years 3 months ago
Discriminative training methods for language models using conditional entropy criteria
This paper addresses the problem of discriminative training of language models that does not require any transcribed acoustic data. We propose to minimize the conditional entropy ...
Jui-Ting Huang, Xiao Li, Alex Acero