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AROBOTS
2011
15 years 2 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
JMLR
2010
103views more  JMLR 2010»
15 years 1 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
ICASSP
2011
IEEE
14 years 10 months ago
Discriminative duration modeling for speech recognition with segmental conditional random fields
This paper describes a new approach to modeling duration for LVCSR using SCARF, a toolkit for speech recognition with segmental conditional random fields. We utilize SCARF’s abi...
Justine T. Kao, Geoffrey Zweig, Patrick Nguyen
ICASSP
2011
IEEE
14 years 10 months ago
Bilingual acoustic modeling with state mapping and three-stage adaptation for transcribing unbalanced code-mixed lectures
This paper presents a bilingual acoustic modeling approach for transcribing Mandarin-English code-mixed lectures with highly unbalanced language distribution. Special terminologie...
Ching-feng Yeh, Liang-Che Sun, Chao-Yu Huang, Lin-...
ICASSP
2011
IEEE
14 years 10 months ago
Factored covariance modeling for text-independent speaker verification
Gaussian mixture models (GMMs) are commonly used to model the spectral distribution of speech signals for text-independent speaker verification. Mean vectors of the GMM, used in c...
Eryu Wang, Kong-Aik Lee, Bin Ma, Haizhou Li, Wu Gu...