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» On the Error Parameter of Dispersers
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PRL
2007
131views more  PRL 2007»
15 years 6 months ago
A new look at discriminative training for hidden Markov models
ct 7 Discriminative training for hidden Markov models (HMMs) has been a central theme in speech recognition research for many years. 8 One most popular technique is minimum classiï...
Xiaodong He, Li Deng
VTC
2010
IEEE
160views Communications» more  VTC 2010»
15 years 4 months ago
Amplify-and-Forward Relaying Aided Reed-Solomon Coded Hybrid-ARQ Relying on Realistic Channel Estimation
Abstract— Channel estimation (CE) plays an important role in determining the achievable performance of coherently detected communications systems. In this paper, the impact of im...
Hoang Anh Ngo, Lajos Hanzo
EMNLP
2010
15 years 4 months ago
Assessing Phrase-Based Translation Models with Oracle Decoding
Extant Statistical Machine Translation (SMT) systems are very complex softwares, which embed multiple layers of heuristics and embark very large numbers of numerical parameters. A...
Guillaume Wisniewski, Alexandre Allauzen, Fran&cce...
ICASSP
2010
IEEE
15 years 4 months ago
Psychoacoustically motivated, frequency dependent Tikhonov regularization for soundfield parametrization
Noise is inevitably introduced during model based parametrization of acoustic fields, acquired using microphone arrays. This is due to the finite number of microphones used, the f...
Deep Sen, Shuai Wang, Andy Deffrasnes
ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
15 years 4 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...