Aphasia is a language disorder that affects the speaking ability of millions of patients. This
paper presents a new benchmark for Aphasia speech recognition and detection tasks using …

In light of medical biases and variability of Aphasia classes, determining the severity of the
Aphasia disorder warrants the use of machine learning to properly leverage patient data for …

Automatic analysis of aphasic speech based on speech technology has been extensively
investigated in recent years, but there has been a few studies on Chinese languages. In this …

Aphasia is a common speech and language disorder, typically caused by a brain injury or a
stroke, that affects millions of people worldwide. Detecting and assessing Aphasia in …

Aphasia, a language disorder resulting from brain damage, requires accurate identification
of specific aphasia types, such as Broca's and Wernicke's aphasia, for effective treatment …

Aphasia, a language disorder primarily caused by a stroke, is traditionally diagnosed using
behavioral language tests. However, these tests are time-consuming, require manual …

Conventionally, automatic assessment of pathological speech involves two main steps:(1)
extraction of pathology-specific features;(2) classification or regression of extracted features …

Robust speech recognition is a key prerequisite for semantic feature extraction in automatic
aphasic speech analysis. However, standard one-size-fits-all automatic speech recognition …

Alzheimer's disease (AD) is a neurodegenerative disease involving the decline of cognitive
ability with illness progresses. At present, the diagnosis of AD mainly depends on the …

Spontaneous speech analysis plays an important role in the study and treatment of aphasia,
but can be difficult to perform manually due to the time consuming nature of speech …