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» Articulatory features for robust visual speech recognition
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ICASSP
2010
IEEE
13 years 7 months ago
Robust spectro-temporal features based on autoregressive models of Hilbert envelopes
In this paper, we present a robust spectro-temporal feature extraction technique using autoregressive models (AR) of sub-band Hilbert envelopes. AR models of Hilbert envelopes are...
Sriram Ganapathy, Samuel Thomas, Hynek Hermansky
CVPR
2005
IEEE
14 years 9 months ago
Object Recognition with Features Inspired by Visual Cortex
We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position- and scale-tolerant edgedetectors ...
Thomas Serre, Lior Wolf, Tomaso Poggio
AAAI
2008
13 years 9 months ago
Unstructured Audio Classification for Environment Recognition
My thesis aims to contribute towards building autonomous agents that are able to understand their surrounding environment through the use of both audio and visual information. To ...
Selina Chu
TASLP
2008
133views more  TASLP 2008»
13 years 6 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....
CVPR
2007
IEEE
14 years 9 months ago
Robust Local Features and their Application in Self-Calibration and Object Recognition on Embedded Systems
In recent years many powerful Computer Vision algorithms have been invented, making automatic or semiautomatic solutions to many popular vision tasks, such as visual object recogn...
Clemens Arth, Christian Leistner, Horst Bischof