Concept

Réseau bayésien dynamique

Publications associées (32)

Probabilistic Graphical Models for Human Interaction Analysis

The objective of this thesis is to develop probabilistic graphical models for analyzing human interaction in meetings based on multimodel cues. We use meeting as a study case of human interactions since research shows that high complexity information is mo ...

École Polytechnique Fédérale de Lausanne2006

Bayesian Networks for Error Handling through Multimodality Fusion in Spoken Dialogues with Mobile Robots

In this paper, we introduce Bayesian networks architecture for combining speech-based information with that from another modality for error handling in human-robot dialogue system. In particular, we report on experiments interpreting speech and laser scann ...

2004

Automatic Speech Recognition using Dynamic Bayesian Networks with the Energy as an Auxiliary Variable

In current automatic speech recognition (ASR) systems, the energy is not used as part of the feature vector in spite of being a fundamental feature in the speech signal. The noise inherent in its estimation degrades the system performance. In this report w ...

IDIAP2003

Speech recognition with auxiliary information

Automatic speech recognition (ASR) is a very challenging problem due to the wide variety of the data that it must be able to deal with. Being the standard tool for ASR, hidden Markov models (HMMs) have proven to work well for ASR when there are controls ov ...

EPFL2003

Speech Recognition with Auxiliary Information

IDIAP2003

Speech Recognition with Auxiliary Information

École Polytechnique Fédérale de Lausanne, Computer Science Department2003

Dynamic Bayesian Network Based Speech Recognition with Pitch and Energy as Auxiliary Variables

Hervé Bourlard

Pitch and energy are two fundamental features describing speech, having importance in human speech recognition. However, when incorporated as features in automatic speech recognition (ASR), they usually result in a significant degradation on recognition pe ...

IDIAP2002

2002

Automatic speech recognition bases its models on the acoustic features derived from the speech signal. Some have investigated replacing or supplementing these features with information that can not be precisely measured (articulator positions, pitch, gende ...

IDIAP2001

Modeling Auxiliary Information in Bayesian Network Based ASR

Hervé Bourlard

2001

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