Abstract Motor Neuron Disease (MND) is a progressive and largely fatal neurodegeneritve
disorder with a lifetime risk of approximately 1 in 300. At diagnosis, up to 25% of people with …

Purpose: Many studies using machine learning (ML) in speech, language, and hearing
sciences rely upon cross-validations with single data splitting. This study's first purpose is to …

Silent speech recognition (SSR) converts nonaudio information such as articulatory
movements into text. SSR has the potential to enable persons with laryngectomy to …

This study examined the relationship (1) between acoustic vowel space and the
corresponding tongue kinematic vowel space and (2) between formant frequencies (F1 and …

Quantification of tongue shape is potentially useful for indexing articulatory strategies arising
from intervention, therapy and development. Tongue shape complexity is a parameter that …

Recent innovations in 3D motion capture technology such as electromagnetic articulography
(EMA) are providing unprecedented access to the intricate movements of the articulators …

Purpose: This research aimed to automatically predict intelligible speaking rate for
individuals with Amyotrophic Lateral Sclerosis (ALS) based on speech acoustic and …

Amyotrophic lateral sclerosis (ALS) is a rapid neurodegenerative disease that affects the
speech motor functions of patients, thus causes dysarthria. There is no definite marker for …

Personalized diagnosis and therapy requires monitoring patient activity using various body
sensors. Sensor data generated during personalized exercises or tasks may be too specific …

Recovering speech in the absence of the acoustic speech signal itself, ie, silent speech,
holds great potential for restoring or enhancing oral communication in those who lost it …