Add to ORKGInternational audienceThis paper addresses the topic of deep neural networks (DNN). Recently, DNN has become a flagship in the fields of artificial intelligence. Deep learning has surpassed state-of-the-art results in many domains: image recognition, speech recognition, language modelling, parsing, information retrieval, speech synthesis, translation, autonomous cars, gaming, etc. DNN have the ability to discover and learn complex structure of very large data sets. Moreover, DNN have a great capability of generalization. More specifically, speech recognition with DNN is the topic of our work in this paper. We present an overview of different architectures and training procedures for DNN-based models. In the framework of transcription of bro...
For most languages in the world and for speech that deviates from the standard pronunciation, not en...
Deep learning and neural network research has grown significantly in the fields of automatic speech ...
Deep neural networks (DNNs) and deep learning approaches yield state-of-the-art performance in a ran...
Over these last few years, the use of Artificial Neural Networks (ANNs), now often referred to as de...
Recently, automatic speech recognition (ASR) systems that use deep neural networks (DNNs) for acoust...
Speech recognition has been an important sector of research to enhance the user interaction with mac...
In this work, we present a comprehensive study on the use of deep neural networks (DNNs) for automat...
The final publication is available at https://link.springer.com/chapter/10.1007%2F978-3-319-49169-1_...
AbstractIn this work, we present a comprehensive study on the use of deep neural networks (DNNs) for...
Abstract — Speech Recognition is the translation of spoken words into text. Speech recognition invol...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
: In this paper, we review the research work that deal with neural network based speech recognition ...
International audienceMost state-of-the-art speech systems use deep neural networks (DNNs). These sy...
International audienceMost state-of-the-art speech systems use deep neural networks (DNNs). These sy...
A defining problem in spoken language identification (LID) is how to design effective representation...
For most languages in the world and for speech that deviates from the standard pronunciation, not en...
Deep learning and neural network research has grown significantly in the fields of automatic speech ...
Deep neural networks (DNNs) and deep learning approaches yield state-of-the-art performance in a ran...
Over these last few years, the use of Artificial Neural Networks (ANNs), now often referred to as de...
Recently, automatic speech recognition (ASR) systems that use deep neural networks (DNNs) for acoust...
Speech recognition has been an important sector of research to enhance the user interaction with mac...
In this work, we present a comprehensive study on the use of deep neural networks (DNNs) for automat...
The final publication is available at https://link.springer.com/chapter/10.1007%2F978-3-319-49169-1_...
AbstractIn this work, we present a comprehensive study on the use of deep neural networks (DNNs) for...
Abstract — Speech Recognition is the translation of spoken words into text. Speech recognition invol...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
: In this paper, we review the research work that deal with neural network based speech recognition ...
International audienceMost state-of-the-art speech systems use deep neural networks (DNNs). These sy...
International audienceMost state-of-the-art speech systems use deep neural networks (DNNs). These sy...
A defining problem in spoken language identification (LID) is how to design effective representation...
For most languages in the world and for speech that deviates from the standard pronunciation, not en...
Deep learning and neural network research has grown significantly in the fields of automatic speech ...
Deep neural networks (DNNs) and deep learning approaches yield state-of-the-art performance in a ran...