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In this work, we propose different strategies for efficiently integrating an automated speech recognition module in the framework of a dialogue-based vocal system. The aim is the study of different ways leading to the improvement of the quality and robustn ...
Within the field of pattern recognition, biometrics is the discipline which is concerned with the automatic recognition of a person based on his/her physiological or behavioral characteristics. Face recognition, a central area in biometrics, is a very chal ...
This paper investigates the use of unlabeled data to help labeled data for audio-visual event recognition in meetings. To deal with situations in which it is difficult to collect enough labeled data to capture event characteristics, but collecting a large ...
This paper investigates the use of unlabeled data to help labeled data for audio-visual event recognition in meetings. To deal with situations in which it is difficult to collect enough labeled data to capture event characteristics, but collecting a large ...
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 ...
The environment that surrounds us is very complex. Understanding and interpreting it is a very hard task. This paper proposes an approach allowing simple form recognition with a camera by using a probabilistic approach called Bayesian Programming. The main ...
The goal of the thesis is to investigate different approaches that combine and integrate Automatic Speech Recognition (ASR) and Speaker Recognition (SR) systems, with applications to (1) User-Customized Password Speaker Verification (UCP-SV) systems, and, ...
Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...
In this paper, we investigate the possibility of enhancing state-of-the-art HMM-based speech recognition systems using data-driven techniques, where whole set of training utterances is used as reference models and recognition is then performed through the ...
In this paper, we investigate the possibility of enhancing state-of-the-art HMM-based speech recognition systems using data-driven techniques, where whole set of training utterances is used as reference models and recognition is then performed through the ...
