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» Temporal Feature Selection for Noisy Speech Recognition
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IROS
2007
IEEE
158views Robotics» more  IROS 2007»
15 years 4 months ago
Feature selection in conditional random fields for activity recognition
Abstract— Temporal classification, such as activity recognition, is a key component for creating intelligent robot systems. In the case of robots, classification algorithms mus...
Douglas L. Vail, John D. Lafferty, Manuela M. Velo...
TASLP
2008
133views more  TASLP 2008»
14 years 8 months ago
Minimum Mean-Squared Error Estimation of Mel-Frequency Cepstral Coefficients Using a Novel Distortion Model
In this paper, a new method for statistical estimation of Mel-frequency cepstral coefficients (MFCCs) in noisy speech signals is proposed. Previous research has shown that model-ba...
Kevin M. Indrebo, Richard J. Povinelli, Michael T....
IMCSIT
2010
14 years 7 months ago
Automatic Detection of Prominent Words in Russian Speech
Abstract--An experimental research with a goal to automatically detect prominent words in Russian speech is presented in this paper. The proposed automatic prominent word detection...
Daniil Kocharov
ICASSP
2009
IEEE
15 years 4 months ago
Bounded conditional mean imputation with Gaussian mixture models: A reconstruction approach to partly occluded features
In this work we show how conditional mean imputation can be bounded through the use of box-truncated Gaussian distributions. That is of interest when signals or features are partl...
Friedrich Faubel, John W. McDonough, Dietrich Klak...
CVPR
2004
IEEE
15 years 12 months ago
Asymmetrically Boosted HMM for Speech Reading
Speech reading, also known as lip reading, is aimed at extracting visual cues of lip and facial movements to aid in recognition of speech. The main hurdle for speech reading is th...
Pei Yin, Irfan A. Essa, James M. Rehg