12 citations · 19 across the 4 of their papers we have counts for
5 papers
Improved Processing of Ultrasound Tongue Videos by Combining ConvLSTM and 3D Convolutional Networks
Amin Honarmandi Shandiz, Laszlo Toth
Silent Speech Interfaces aim to reconstruct the acoustic signal from a sequence of ultrasound tongue images that records the articulatory movement. The extraction of information ab…
3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfaces
László Tóth, Amin Honarmandi Shandiz
Silent speech interfaces (SSI) aim to reconstruct the speech signal from a recording of the articulatory movement, such as an ultrasound video of the tongue. Currently, deep neural…
Ultrasound-based Silent Speech Interface Built on a Continuous Vocoder
Tamás Gábor Csapó, Mohammed Salah Al-Radhi, Géza Németh +4
Recently it was shown that within the Silent Speech Interface (SSI) field, the prediction of F0 is possible from Ultrasound Tongue Images (UTI) as the articulatory input, using Dee…
Autoencoder-Based Articulatory-to-Acoustic Mapping for Ultrasound Silent Speech Interfaces
Gábor Gosztolya, Ádám Pintér, László Tóth +3
When using ultrasound video as input, Deep Neural Network-based Silent Speech Interfaces usually rely on the whole image to estimate the spectral parameters required for the speech…
GMM-Free Flat Start Sequence-Discriminative DNN Training
Gábor Gosztolya, Tamás Grósz, László Tóth
Recently, attempts have been made to remove Gaussian mixture models (GMM) from the training process of deep neural network-based hidden Markov models (HMM/DNN). For the GMM-free tr…