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» Phoneme recognition using Boosted Binary Features
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CVPR
2007
IEEE
14 years 7 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 5 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
13 years 11 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
13 years 11 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 5 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