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HMM-Based Error Correction Mechanism for Five-Key Chording Keyboards

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Error Correction Mechanism for Five-Key Chording Keyboards

Pierre Dillenbourg, Bixio Rimoldi, Adrian Dan Tarniceriu

As different text input devices lead to different typing error patterns, considering the device characteristics when designing an error correction mechanism can lead to significantly improved results. In this paper, we propose and evaluate a spelling algor ...

IEEE2013

Statistical models for HMM/ANN hybrids

Philip Neil Garner, David Imseng

We present a theoretical investigation into the use of normalised artificial neural network (ANN) outputs in the context of hidden Markov models (HMMs). The work is motivated by the pursuit of a more theoretically rigorous understanding of the Kullback-Lie ...

Idiap2013

Randomized Low-Memory Singular Value Projection

Volkan Cevher, Anastasios Kyrillidis

Affine rank minimization algorithms typically rely on calculating the gradient of a data error followed by a singular value decomposition at every iteration. Because these two steps are expensive, heuristics are often used for approximations that reduce co ...

2013

Feature distribution modelling techniques for 3D face recognition

Sébastien Marcel

This paper shows that Hidden Markov Models (HMMs) can be effectively ap- plied to 3D face data. The examined HMM techniques are shown to be superior to a previously examined Gaussian Mixture Model (GMM) technique. Experi- ments conducted on the Face Recogn ...

2010

Markov Chain Modeling And Analysis Of Complicated Phenomena In Coupled Chaotic Oscillators

Martin Hasler

In this paper, we propose a Markov chain modeling of complicated phenomena observed from coupled chaotic oscillators. Once we obtain the transition probability matrix from computer simulation results, various statistical quantities can be easily calculated ...

2010

Evaluation of a probabilistic approach to learn and reproduce gestures by imitation

Aude Billard, Sylvain Calinon, Eric Sauser

We present an approach based on Hidden Markov Model (HMM) and Gaussian Mixture Regression (GMR) to learn robust models of human motion through imitation. The proposed approach allows us to extract redundancies across multiple demonstrations and build time- ...

2010

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

Boosting word error rates

Samy Bengio, Christos Dimitrakakis

2005

From Error Probability to Information Theoretic (Multi-Modal) Signal Processing

Jean-Philippe Thiran, Torsten Butz

We propose an information theoretic model that unifies a wide range of existing information theoretic signal processing algorithms in a compact mathematical framework. It is mainly based on stochastic processes, Markov chains and error probabilities. The p ...

2005

Local Features and 1D-HMMs for Fast and Robust Face Authentication

It has been previously demonstrated that systems based on Hidden Markov Models (HMMs) are suitable for face recognition. The proposed approaches in the literature are either HMMs with one-dimensional (1D-HMMs) or two-dimensional (2D-HMMs) topology. Both ha ...

IDIAP2005