Publication

Confusion Matrix Based Entropy Correction in Multi-stream Combination

Related publications (57)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Investigation of kNN Classifier on Posterior Features Towards Application in Automatic Speech Recognition

Hervé Bourlard, Afsaneh Asaei, Benjamin Picart

Class posterior distributions can be used to classify or as intermediate features, which can be further exploited in different classifiers (e.g., Gaussian Mixture Models, GMM) towards improving speech recognition performance. In this paper we examine the p ...

Idiap2010

Reid et al.'s distance bounding protocol and mafia fraud attacks over noisy channels

Christos Dimitrakakis

Distance bounding protocols are an effective countermeasure against relay attacks including distance fraud, mafia fraud and terrorist fraud attacks. Reid et al. proposed the first symmetric key distance bounding protocol against mafia and terrorist fraud a ...

2010

Support Vector Machines with a Reject Option

We consider the problem of binary classification where the classfier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow’s rule, is deﬁned by two thresholds on posterior probabilities. From simple desi ...

Idiap2009

MLP Based Hierarchical System for Task Adaptation in ASR

Hervé Bourlard, Joel Praveen Pinto

We investigate a multilayer perceptron (MLP) based hierarchical approach for task adaptation in automatic speech recognition. The system consists of two MLP classifiers in tandem. A well-trained MLP available off-the-shelf is used at the first stage of the ...

2009

Support Vector Machines with a Reject Option

We consider the problem of binary classification where the classifier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow’s rule, is deﬁned by two thresholds on posterior probabilities. From simple des ...

2008

Bayesian Inference for Spiking Neuron Models with a Sparsity Prior

Matthias Seeger, Matthias Bethge

Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the expectation propagation algorithm, we are able to approximate the full poster ...

2008

Acoustic models for posterior features in speech recognition

Guillermo Aradilla

In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...

EPFL2008

Acoustic Models for Posterior Features in Speech Recognition

Guillermo Aradilla

Ecole Polytechnique Fédérale de Lausanne2008

Acoustic Models for Posterior Features in Speech Recognition

Guillermo Aradilla

Idiap2008

Optimisation of a Thick-Film 10...400 N Force Sensor

Peter Ryser, Thomas Maeder, Giancarlo Corradini, Niklaus Johner, Gregory Affolter

Abstract: The ring-on-ring bending principle allows the fabrication of simple, low-cost thick-film piezoresistive sensors for compressive forces in the 10 to 400 N range. However some imperfections are encountered in its basic embodiment, such as relativel ...

Elsevier2008