ListarIngeniería por tema "Deep learning"
Mostrando ítems 1-19 de 19
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A performance evaluation of several artificial neural networks for mapping speech spectrum parameters
(2020)In this work, we compare different neural network architectures, for the task of mapping spectral coefficients of noisy speech signals with those corresponding to natural speech. In previous works on the subject, fully-connected ... -
Alzheimer’s Disease Early Detection Using a Low Cost Three-Dimensional Densenet-121 Architecture
(2020-06-23)The objective of this work is to detect Alzheimer’s disease using Magnetic Resonance Imaging. For this, we use a three-dimensional densenet-121 architecture. With the use of only freely available tools, we obtain good ... -
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, ... -
An Experimental Study on Speech Enhancement Based on a Combination of Wavelets and Deep Learning
(2022-06-20)The purpose of speech enhancement is to improve the quality of speech signals degraded by noise, reverberation, or other artifacts that can affect the intelligibility, automatic recognition, or other attributes involved ... -
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 ... -
Desarrollo de Tecnologías del Habla en Costa Rica
(2020)Las tecnologías del habla son un conjunto de conocimientos, técnicas y recursos empleados para propiciar la interacción de las personas con dispositivos electrónicos, o bien entre personas con mediación de un dispositivo. ... -
Discriminative multi-stream postfilters based on deep learning for enhancing statistical parametric speech synthesis
(2021)Statistical parametric speech synthesis based on Hidden Markov Models has been an important technique for the production of artificial voices, due to its ability to produce results with high intelligibility and sophisticated ... -
Evaluation of Mixed Deep Neural Networks for Reverberant Speech Enhancement
(2020)Speech signals are degraded in real-life environments, as a product of background noise or other factors. The processing of such signals for voice recognition and voice analysis systems presents important challenges. One ... -
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 ... -
HMM-Based Speech Synthesis Enhancement with Hybrid Postfilters
(2018)In this chapter, we introduce hybrid postfilters into speech synthesis, with the objective of enhancing the quality of the synthesized speech. Our approach combines a Wiener filter with deep neural networks. Several ... -
Hybrid speech enhancement with wiener filters and deep LSTM denoising autoencoders
(2018)Over the past several decades, numerous speech enhancement techniques have been proposed to improve the performance of modern communication devices in noisy environments. Among them, there is a large range of classical ... -
Improving automatic speech recognition containing additive noise using deep denoising autoencoders of lstm networks
(2016)Automatic speech recognition systems (ASR) suffer from performance degradation under noisy conditions. Recent work, using deep neural networks to denoise spectral input features for robust ASR, have proved to be successful. ... -
Improving post-filtering of artificial speech using pre-trained LSTM neural networks
(2019)Several researchers have contemplated deep learning-based post-filters to increase the quality of statistical parametric speech synthesis, which perform a mapping of the synthetic speech to the natural speech, considering ... -
LSTM deep neural networks postfiltering for enhancing synthetic voices
(2018)Recent developments in speech synthesis have produced systems capable of producing speech which closely resembles natural speech, and researchers now strive to create models that more accurately mimic human voices. One ... -
LSTM deep neural networks postfiltering for improving the quality of synthetic voices
(2016)Recent developments in speech synthesis have produced systems capable of providing intelligible speech, and researchers now strive to create models that more accurately mimic human voices. One such development is the ... -
Pre-training Long Short-term Memory neural networks for efficient regression in artificial speech postfiltering
(2018)Several attempts to enhance statistical parametric speech synthesis have contemplated deep-learning-based postfilters, which learn to perform a mapping of the synthetic speech parameters to the natural ones, reducing the ... -
Reconstructing fundamental frequency from noisy speech using initialized autoencoders
(2020-10)In this paper, we present a new approach for fundamental frequency (f0) detection in noisy speech, based on Long Short-term Memory Neural Networks (LSTM). f0 is one of the most important parameters of human speech. Its ... -
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 ... -
Speech synthesis based on Hidden Markov Models and deep learning
(2016)Speech synthesis based on Hidden Markov Models (HMM) and other statistical parametric techniques have been a hot topic for some time. Using this techniques, speech synthesizers are able to produce intelligible and ...