Low-Rank Representation For Enhanced Deep Neural Network Acoustic Models
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In this paper, we further investigate the large vocabulary continuous speech recognition approach to keyword spotting. Given a speech utterance, recognition is performed to obtain a word lattice. The posterior probability of keyword hypotheses in the latti ...
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 ...
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 ...
This paper investigates the use of features based on posterior probabilities of subword units such as phonemes. These features are typically transformed when used as inputs for a hidden Markov model with mixture of Gaussians as emission distribution (HMM/G ...
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 ...
EPFL2006
This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...
This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...
This paper investigates the use of features based on posterior probabilities of subword units such as phonemes. These features are typically transformed when used as inputs for a hidden Markov model with mixture of Gaussians as emission distribution (HMM/G ...
This paper discusses and optimizes an HMM/GMM based User-Customized Password Speaker Verification (UCP-SV) system. Unlike text-dependent speaker verification, in UCP-SV systems, customers can choose their own passwords with no lexical constraints. The pass ...
Local state or phone posterior probabilities are often investigated as local scores (e.g., hybrid HMM/ANN systems) or as transformed acoustic features (e.g., ``Tandem'') to improve speech recogni tion systems. In this paper, we present initial results towa ...
