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Class-specific classifiers in audio-visual speech recognition

Publications associées (32)

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A multimodal pattern recognition framework for speaker detection

Patricia Besson

Speaker detection is an important component of a speech-based user interface. Audiovisual speaker detection, speech and speaker recognition or speech synthesis for example find multiple applications in human-computer interaction, multimedia content indexin ...

EPFL2007

Relevant Feature Selection for Audio-Visual Speech Recognition

Jean-Philippe Thiran, Mihai Gurban, Thomas Drugman

We present a feature selection method based on information theoretic measures, targeted at multimodal signal processing, showing how we can quantitatively assess the relevance of features from different modalities. We are able to find the features with the ...

2007

Information theoretic combination of classifiers with application to face detection

Julien Meynet

Combining several classifiers has become a very active subdiscipline in the field of pattern recognition. For years, pattern recognition community has focused on seeking optimal learning algorithms able to produce very accurate classifiers. However, empiri ...

EPFL2007

Non-linear Spectral Contrast Stretching for In-car Speech Recognition

Hervé Bourlard, Weifeng Li

In this paper, we present a novel feature normalization method in the log-scaled spectral domain for improving the noise robustness of speech recognition front-ends. In the proposed scheme, a non-linear contrast stretching is added to the outputs of log me ...

2007

Non-linear Spectral Contrast Stretching for In-car Speech Recognition

Hervé Bourlard, Weifeng Li

IDIAP2007

Ensembles for sequence learning

Christos Dimitrakakis

This thesis explores the application of ensemble methods to sequential learning tasks. The focus is on the development and the critical examination of new methods or novel applications of existing methods, with emphasis on supervised and reinforcement lear ...

EPFL2007

Ensembles for Sequence Learning

Christos Dimitrakakis

École Polytechnique Fédérale de Lausanne2006

Mutual information eigenlips for audio-visual speech recognition

Jean-Philippe Thiran, Ivana Arsic de Heras Ciechomska

This paper proposes an application of information theoretic approach for finding the most informative subset of eigenfeatures to be used for audio-visual speech recognition tasks. The state-of-the-art visual feature extraction methods in the area of speech ...

IEEE2006

Audio-Visual Speech Recognition with a Hybrid SVM-HMM System

Jean-Philippe Thiran, Mihai Gurban

Traditional speech recognition systems use Gaussian mixture models to obtain the likelihoods of individual phonemes, which are then used as state emission probabilities in hidden Markov models representing the words. In hybrid systems, the Gaussian mixture ...

EUSIPCO2005

Boosting HMMs with an application to speech recognition

Samy Bengio, Christos Dimitrakakis

Boosting is a general method for training an ensemble of classifiers with a view to improving performance relative to that of a single classifier. While the original AdaBoost algorithm has been defined for classification tasks, the current work examines it ...

2004