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Boosting word error rates

Publications associées (39)

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Stochastic modeling in sediment dynamics: Exner equation for planar bed incipient bed load transport conditions

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Even under flow equilibrium conditions, river bed topography continuously evolves with time, producing trains of irregular bed forms. The idea has recently emerged that the variability in the bed form geometry results from some randomness in sediment flux. ...

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Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009

Sliding Window Abstraction for Infinite Markov Chains

Maria-Emanuela-Canini Mateescu, Verena Wolf

We present an on-the-fly abstraction technique for infinite-state continuous-time Markov chains. We consider Markov chains that are specified by a finite set of transition classes. Such models naturally represent biochemical reactions and therefore play an ...

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Most discriminative techniques for detecting instances from object categories in still images consist of looping over a partition of a pose space with dedicated binary classifiers. The efficiency of this strategy for a complex pose, i.e., for fine-grained ...

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Stationary Features and Cat Detection

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IDIAP2007

Ensembles for sequence learning

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Using Posterior-Based Features in Template Matching for Speech Recognition

Hervé Bourlard, Guillermo Aradilla

Given the availability of large speech corpora, as well as the increasing of memory and computational resources, the use of template matching approaches for automatic speech recognition (ASR) have recently attracted new attention. In such template-based ap ...

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Using Posterior-Based Features in Template Matching for Speech Recognition

Hervé Bourlard, Guillermo Aradilla

IDIAP2006

Ensembles for Sequence Learning

Christos Dimitrakakis

École Polytechnique Fédérale de Lausanne2006

Boosting word error rates

Samy Bengio, Christos Dimitrakakis

We apply boosting techniques to the problem of word error rate minimisation in speech recognition. This is achieved through a new definition of sample error for boosting and a training procedure for hidden Markov models. For this purpose we define a sample ...

2005