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Iris de Fisher

Publications associées (34)

Fast high-dimensional Bayesian classification and clustering

We introduce a fast approach to classification and clustering applicable to high-dimensional continuous data, based on Bayesian mixture models for which explicit computations are available. This permits us to treat classification and clustering in a single ...

EPFL2009

Partitioning Datasets Based on Equalities Among Parameters

Giancarlo Ferrari Trecate

When a phenomenon is described by a parametric model and multiple datasets are available, a key problem in statistics is to discover which datasets are characterized by the same parameter values. Equivalently, one is interested in partitioning the family o ...

2009

An Information Theoretic Approach to Speaker Diarization of Meeting Data

Hervé Bourlard, Fabio Valente, Deepu Vijayasenan

A speaker diarization system based on an information theoretic framework is described. The problem is formulated according to the Information Bottleneck (IB) principle. Unlike other approaches where the distance between speaker segments is arbitrarily intr ...

2009

Assessing the effectiveness of slides as a mean to improve the automatic transcription of oral presentations

Hervé Bourlard, Artem Peregoudov, Alessandro Vinciarelli

This paper presents experiments aiming at improving the automatic transcription of oral presentations through the inclusion of the slides in the recognition process. The experiments are performed over a data set of around three hours of material (~33 kword ...

IDIAP2006

Single-linkage clustering for optimal classification in piecewise affine regression

Giancarlo Ferrari Trecate

When performing regression with piecewise affine maps, the most challenging task is to classify the data points, i.e. to correctly attribute a data point to the affine submodel that most likely generated it. In this paper, we consider a regression scheme s ...

2003

Evaluation of Formant-Like Features for ASR

Hervé Bourlard, Samy Bengio, Katrin Weber

This paper investigates possibilities to automatically find a low-dimensional, formant-related physical representation of the speech signal, which is suitable for automatic speech recognition (ASR). This aim is motivated by the fact that formants have been ...

IDIAP2002

Evaluation of Formant-Like Features for ASR

Hervé Bourlard, Samy Bengio, Katrin Weber

2002

Speech Recognition Using Advanced HMM2 Features

Hervé Bourlard, Samy Bengio, Katrin Weber

HMM2 is a particular hidden Markov model where state emission probabilities of the temporal (primary) HMM are modeled through (secondary) state-dependent frequency-based HMMs [12]. As shown in [13], a secondary HMM can also be used to extract robust ASR fe ...

IDIAP2001

Speech Recognition Using Advanced HMM2 Features

Hervé Bourlard, Samy Bengio, Katrin Weber

2001

Mixture models for unsupervised and supervised learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

EPFL2000

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