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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 ...
A new likelihood method to estimate the extremal index, together with an application to temperature data, is presented. Conditions for the validity of the model are discussed and diagnostics are proposed. ...
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 ...
The article develops the approach of Ferro and Segers (2003) to the estimation of the extremal index, and proposes the use of a new variable decreasing the bias of the likelihood based on the point process character of the exceedances. Two estimators are d ...
Biometric authentication can be cast as a signal processing and statistical pattern recognition problem. As such, it relies on models of signal representations that can be used to discriminate between classes. One of the assumptions typically made by the p ...
We outline how modern likelihood theory, which provides essentially exact inferences in a variety of parametric statistical problems, may routinely be applied in practice. Although the likelihood procedures are based on analytical asymptotic approximations ...
A method is proposed to robabilistically map location observations to the underlying network. Instead of generating a single path as the map matching algorithms do, this method aims at calculating a likelihood for each potentially true path to have been th ...
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 ...
A method is proposed to probabilistically map location observations to the underlying network. Instead of generating a single path as the map matching algorithms do, this method aims at calculating a likelihood for each potentially true path to have been t ...
Facial expression recognition by human observers is affected by subjective components. Indeed there is no ground truth. We have developped Discrete Choice Models to capture the human perception of facial expressions. In a first step, the static case is tre ...
