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 …

Self-Supervised Learning (SSL) based models of speech have shown remarkable
performance on a range of downstream tasks. These state-of-the-art models have remained …

The goal of this work is to investigate the correlation between physiological process of
articulation and emotion expressing modes via speech of Mandarin Chinese. A bimodal …

This paper presents a novel deep autoregressive method for Acoustic-to-Articulatory
Inversion called Articulatory-WaveNet. In traditional methods such as Gaussian Mixture …

A multi-modal emotional speech Mandarin database including articulatory kinematics,
acoustics, glottal and facial micro-expressions is designed and established, which is …

This paper aims to utilize a deep reinforcement learning algorithm for the acoustic-to-
articulatory inversion problem. A deep deterministic policy gradient (DDPG) based method is …

In this paper we introduce a new speaker independent method for Acoustic-to-Articulatory
Inversion. The proposed architecture, Speaker Independent-Articulatory WaveNet (SI-AWN) …

Many people with Parkinson's disease suffer from speech problems, but we do not quite
know where these problems come from. In the current dissertation, we investigated two …

This paper presents Articulatory-WaveNet, a new approach for acoustic-to-articulator
inversion. The proposed system uses the WaveNet speech synthesis architecture, with …

This paper presents an electromagnetic articulography database of Japanese sentences.
The database includes aligned acoustics and articulatory data from seven males and three …