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A risk-based methodology for defining the time of intentional controlled islanding
(2015-10-05)
Power systems are operated close to their stability limits and this increases the probability of cascading outages
leading to large-area blackouts. To mitigate these phenomena, intentional controlled islanding (ICI) has ...
Auto-Associative Initialization of LSTM Neural Networks for Fundamental Frequency Detection in Noisy Speech Signals
(2018)
In this paper, we present a new approach for fundamental frequency detection in noisy speech, based on Long Short-term Memory Neural Networks (LSTM). Fundamental frequency is one of the most important parameters of human ...
Torque sensor geometry study on 3D simulated conditions for a Hollow robotic joint
(2019)
El sensor de torque es el componente que le brinda a una articulación robótica la
capacidad de ser amigable con su entorno, ya que posibilita a un brazo robótico a tomar acciones al
captar disturbios externos mientras ...
Analysis of Atomic Manipulation Tasks in human- shared scenarios (a Kitchen and a Collaborative Workshop Table) for a Humanoid Robot
(2018)
In this paper we analyze the vocabulary of an
action description language to be used, together with a low level
object controller, by a humanoid robot in two specific scenarios:
a kitchen and a collaborative workshop ...
An experimental study on fundamental frequency detection in reverberated speech with pre-trained recurrent neural networks
(2020)
The detection of the fundamental frequency (f0) in speech signals is relevant in areas such as automatic speech recognition and identification, with multiple potential applications. For example, in virtual assistants, ...
Smart placement of a two-arm assembly for an everyday object manipulation humanoid robot based on capability maps
(2018)
A robot that will execute everyday object manip-
ulation tasks needs a competent body that can handle as many
different objects as possible in as many ways as possible. To
accomplish this, we must design the robot body ...
Assessing the robustness of recurrent neural networks to enhance the spectrum of reverberated speech
(2020)
Implementing voice recognition systems and voice analysis in real-life contexts present important challenges, especially when signal recording/registering conditions are adverse. One of the conditions that produce signal ...
Automatic Translation of Spanish Natural Language Commands to Control Robot Comands Based on LSTM Neural Network
(2019)
In this paper, we propose a high level layer able to
translate motion commands in natural spanish language to a
formal intermediate representation called Robot Control
Language (RCL). The layer was built by using the ...
Experimental study on transfer learning in denoising autoencoders for speech enhancement
(2020)
The quality of speech signals is affected by a combination of background noise, reverberation, and other distortions in real-life environments. The processing of such signals presents important challenges for tasks such ...
Robustness of LSTM neural networks for the enhancement of spectral parameters in noisy speech signals
(2019)
In this paper, we carry out a comparative performance analysis of Long Short-term Memory (LSTM) Neural Networks for the task of noise reduction. Recent work in this area has shown the advantages of this kind of network for ...