Deep Neural Networks for Multiple Speaker Detection and Localization
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
We investigate a vocoder based on artificial neural networks using a phonological speech representation. Speech decomposition is based on the phonological encoders, realised as neural network classifiers, that are trained for a particular language. The spe ...
We investigate a vocoder based on artificial neural networks using a phonological speech representation. Speech decomposition is based on the phonological encoders, realised as neural network classifiers, that are trained for a particular language. The spe ...
Automatic recognition of gestures using computer vision is important for many real-world applications such as sign language recognition and human-robot interaction (HRI). Our goal is a real-time hand gesture-based HRI interface for mobile robots. We use a ...
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Markov networks, yielding a powerful and scalable probabilistic model that we ap ...
The use of spaceborne medium resolution imaging spectrometers with neural network algorithms has proven a large potential for application with optically complex inland waters. We make use of this approach to investigate the bio-physical dynamics in a eutro ...
The impact of Phase Change Memory (PCM) as well as other Non-Volatile Memory (NVM) device characteristics on the quantitative classification performance of artificial neural networks is studied. Our results show that any NVM-based neural network — not just ...
This study proposes a new technique for real-time building energy modelling and event detection using kernel regression. We show that this technique can exceed the performance of conventional neural network algorithms, and do so by a large margin when the ...
This paper extends prior work using Compositional Pattern Producing Networks (CPPNs) as a generative encoding for the purpose of simultaneously evolving robot morphology and control. A method is presented for translating CPPNs into complete robots includin ...
Animals have to coordinate a large number of muscles in different ways to efficiently move at various speeds and in different and complex environments. This coordination is in large part based on central pattern generators (CPGs). These neural networks are ...
The manual design of con- trol systems for robotic devices can be challenging. Methods for the automatic synthesis of control systems, such as the evolution of artificial neural networks, are thus widely used in the robotics community. However, in many rob ...
Institute of Electrical and Electronics Engineers2010
