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» Phoneme recognition using Boosted Binary Features
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CVPR
2007
IEEE
14 years 9 months ago
Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition
It is well known that how to extract dynamical features is a key issue for video based face analysis. In this paper, we present a novel approach of facial action units (AU) and ex...
Peng Yang, Qingshan Liu, Dimitris N. Metaxas
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 1 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
ICASSP
2008
IEEE
14 years 1 months ago
Exploiting contextual information for improved phoneme recognition
In this paper, we investigate the significance of contextual information in a phoneme recognition system using the hidden Markov model - artificial neural network paradigm. Cont...
Joel Pinto, B. Yegnanarayana, Hynek Hermansky, Mat...
ICASSP
2010
IEEE
13 years 7 months ago
Comparison of modulation features for phoneme recognition
In this paper, we compare several approaches for the extraction of modulation frequency features from speech signal using a phoneme recognition system. The general framework in th...
Sriram Ganapathy, Samuel Thomas, Hynek Hermansky