This review summarises the status of silent speech interface (SSI) research. SSIs rely on non-
acoustic biosignals generated by the human body during speech production to enable …

Use of artificial intelligence (AI) is a burgeoning field in otolaryngology and the
communication sciences. A virtual symposium on the topic was convened from Duke …

Speech is a complex process involving a wide range of biosignals, including but not limited
to acoustics. These biosignals-stemming from the articulators, the articulator muscle …

This paper gives a general overview of hidden Markov model (HMM)-based speech
synthesis, which has recently been demonstrated to be very effective in synthesizing …

This paper presents a new spectral modeling method for statistical parametric speech
synthesis. In the conventional methods, high-level spectral parameters, such as mel-cepstra …

This paper serves as an initial announcement of the availability of a corpus of articulatory
data called mngu0. This corpus will ultimately consist of a collection of multiple sources of …

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 …

Recent advances in real-time magnetic resonance imaging (RT-MRI) have made it possible
to study the anatomy and dynamic motion of the vocal tract during speech production with …

Estimating articulatory movements from speech acoustic features is known as acoustic-to-
articulatory inversion (AAI). Large amount of parallel data from speech and articulatory …

We implement two deep architectures for the acoustic-articulatory inversion mapping
problem: a deep neural network and a deep trajectory mixture density network. We find that …