Technology that translates neural activity into speech would be transformative for people
who are unable to communicate as a result of neurological impairments. Decoding speech …

This paper reviews data collection practices in electromagnetic articulography (EMA)
studies, with a focus on sensor placement. It consists of three parts: in the first part, we …

When speaking, we dynamically coordinate movements of our jaw, tongue, lips, and larynx.
To investigate the neural mechanisms underlying articulation, we used direct cortical …

While audio-visual speech models can yield superior performance and robustness
compared to audio-only models, their development and adoption are hindered by the lack of …

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 …

In the articulatory synthesis task, speech is synthesized from input features containing
information about the physical behavior of the human vocal tract. This task provides a …

Modeling speech production and speech articulation is still an evolving research topic.
Some current core questions are: What is the underlying (neural) organization for controlling …

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 …

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 …

Canonical correlation analysis (CCA) and kernel CCA can be used for unsupervised
learning of acoustic features when a second view (eg, articulatory measurements) is …