[HTML][HTML] The potential for a speech brain–computer interface using chronic electrocorticography
A brain–computer interface (BCI) is a technology that uses neural features to restore or
augment the capabilities of its user. A BCI for speech would enable communication in real …
augment the capabilities of its user. A BCI for speech would enable communication in real …
Statistical parametric speech synthesis using deep neural networks
Conventional approaches to statistical parametric speech synthesis typically use decision
tree-clustered context-dependent hidden Markov models (HMMs) to represent probability …
tree-clustered context-dependent hidden Markov models (HMMs) to represent probability …
Deep mixture density networks for acoustic modeling in statistical parametric speech synthesis
Statistical parametric speech synthesis (SPSS) using deep neural networks (DNNs) has
shown its potential to produce naturally-sounding synthesized speech. However, there are …
shown its potential to produce naturally-sounding synthesized speech. However, there are …
EMG-to-speech: Direct generation of speech from facial electromyographic signals
Silent speech interfaces are systems that enable speech communication even when an
acoustic signal is unavailable. Over the last years, public interest in such interfaces has …
acoustic signal is unavailable. Over the last years, public interest in such interfaces has …
A deep recurrent approach for acoustic-to-articulatory inversion
To solve the acoustic-to-articulatory inversion problem, this paper proposes a deep
bidirectional long short term memory recurrent neural network and a deep recurrent mixture …
bidirectional long short term memory recurrent neural network and a deep recurrent mixture …
Speaker-independent acoustic-to-articulatory speech inversion
To build speech processing methods that can handle speech as naturally as humans,
researchers have explored multiple ways of building an invertible mapping from speech to …
researchers have explored multiple ways of building an invertible mapping from speech to …
Multi-view CCA-based acoustic features for phonetic recognition across speakers and domains
Canonical correlation analysis (CCA) and kernel CCA can be used for unsupervised
learning of acoustic features when a second view (eg, articulatory measurements) is …
learning of acoustic features when a second view (eg, articulatory measurements) is …
The use of articulatory movement data in speech synthesis applications: An overview—application of articulatory movements using machine learning algorithms—
This paper describes speech processing work in which articulator movements are used in
conjunction with the acoustic speech signal and/or linguistic information. By ''articulator …
conjunction with the acoustic speech signal and/or linguistic information. By ''articulator …
Acoustic-to-articulatory mapping with joint optimization of deep speech enhancement and articulatory inversion models
AS Shahrebabaki, G Salvi, T Svendsen… - … on Audio, Speech …, 2021 - ieeexplore.ieee.org
We investigate the problem of speaker independent acoustic-to-articulatory inversion (AAI)
in noisy conditions within the deep neural network (DNN) framework. In contrast with recent …
in noisy conditions within the deep neural network (DNN) framework. In contrast with recent …
Data driven articulatory synthesis with deep neural networks
S Aryal, R Gutierrez-Osuna - Computer Speech & Language, 2016 - Elsevier
The conventional approach for data-driven articulatory synthesis consists of modeling the
joint acoustic-articulatory distribution with a Gaussian mixture model (GMM), followed by a …
joint acoustic-articulatory distribution with a Gaussian mixture model (GMM), followed by a …