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» Learning Models for Predicting Recognition Performance
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ACMICEC
2006
ACM
157views ECommerce» more  ACMICEC 2006»
14 years 4 months ago
Adaptive mechanism design: a metalearning approach
Auction mechanism design has traditionally been a largely analytic process, relying on assumptions such as fully rational bidders. In practice, however, bidders often exhibit unkn...
David Pardoe, Peter Stone, Maytal Saar-Tsechansky,...
CICLING
2008
Springer
14 years 7 days ago
Semantic and Syntactic Features for Dutch Coreference Resolution
We investigate the effect of encoding additional semantic and syntactic information sources in a classification-based machine learning approach to the task of coreference resolutio...
Iris Hendrickx, Véronique Hoste, Walter Dae...
LREC
2008
119views Education» more  LREC 2008»
13 years 11 months ago
Text Independent Speaker Identification in Multilingual Environments
Speaker identification and verification systems have a poor performance when model training is done in one language while the testing is done in another. This situation is not unu...
Iker Luengo, Eva Navas, Iñaki Sainz, Ibon S...
ICASSP
2011
IEEE
13 years 2 months ago
Feature normalization for speaker verification in room reverberation
The performance of a typical speaker verification system degrades significantly in reverberant environments. This degradation is partly due to the conventional feature extractio...
Sriram Ganapathy, Jason W. Pelecanos, Mohamed Kama...
MOBISYS
2010
ACM
14 years 17 days ago
Darwin phones: the evolution of sensing and inference on mobile phones
We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on ...
Emiliano Miluzzo, Cory Cornelius, Ashwin Ramaswamy...