This paper presents a novel approach for automated dysarthria detection and severity
assessment using a variable short-time Fourier transform layered convolutional neural …

Dysarthria is a speech disorder that affects the ability to communicate due to articulation
difficulties. This research proposes a novel method for automatic dysarthria detection (ADD) …

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 …

Self-supervised learning (SSL) based speech foundation models have been applied to a
wide range of ASR tasks. However, their application to dysarthric and elderly speech via …

Articulatory features are inherently invariant to acoustic signal distortion and have been
successfully incorporated into automatic speech recognition (ASR) systems for normal …

Dysarthria is a medical condition that impairs an individual's ability to speak clearly due to
muscle weakness or paralysis. To diagnose and monitor dysarthria severity, this article …

This paper introduces a novel combination of two tasks, previously treated separately:
acoustic-to-articulatory speech inversion (AAI) and phoneme-to-articulatory (PTA) motion …

We present a novel speaker-independent acoustic-to-articulatory inversion (AAI) model,
overcoming the limitations observed in conventional AAI models that rely on acoustic …

Articulatory features are inherently invariant to acoustic signal distortion and have been
successfully incorporated into automatic speech recognition (ASR) systems designed for …

Acoustic-to-articulatory inversion (AAI) involves mapping from the acoustic to the articulatory
space. Signal-processing features like the MFCCs, have been widely used for the AAI task …