Audio-visual speech recognition (AVSR) system is thought to be one of the most promising
solutions for reliable speech recognition, particularly when the audio is corrupted by noise …

In this work we present a new approach to the field of weakly supervised learning in the
video domain. Our method is relevant to sequence learning problems which can be split up …

A method and also a configuration for determining a descriptive feature of a speech signal,
in which a first speech model is trained with a first time pattern and a second speech model …

In this article we review several successful extensions to the standard hidden-Markov-
model/artificial neural network (HMM/ANN) hybrid, which have recently made important …

In the framework of hidden Markov models (HMM) or hybrid HMM/artificial neural network
(ANN) systems, we present a new approach towards automatic speech recognition (ASR) …

In this study, we propose a novel deep neural network (DNN) architecture for speech
enhancement (SE) via a multiobjective learning and ensembling (MOLE) framework to …

We address the theoretical and practical issues involved in automatic speech recognition
(ASR) when some of the observation data for the target signal is masked by other signals …

Automatic speech recognition enables a wide range of current and emerging applications
such as automatic transcription, multimedia content analysis, and natural human-computer …

Video semantic analysis is essential in video indexing and structuring. However, due to the
lack of robust and generic algorithms, most of the existing works on semantic analysis are …

The so-called tandem approach, where the posteriors of a multilayer perceptron (MLP)
classifier are used as features in an automatic speech recognition (ASR) system has proven …