This chapter provides an overview of inter-disciplinary research works on automatic
assessment of speech and language impairment in spoken discourse. Automatic …

Alzheimer's disease (AD) is the most common form of dementia, affecting millions of
individuals worldwide. Early identification and treatment of AD are critical for advanced …

Aphasia is a condition resulting from a stroke or injury to the brain. This condition renders
the patient unable to use language efficiently. Machine learning and artificial intelligence …

Assessing the severity level of dysarthria can provide an insight into the patient's
improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech …

Due to age-bound onset of symptoms used for diagnosis of mild to moderate intellectual
disability, early diagnosis of these problems has long been a difficult issue. The diagnosis …

Alzheimer's disease (AD) affects more than six million Americans and is the seventh leading
cause of death in the United States. Artificial intelligence (AI), specifically natural language …

Objective: Individuals with aphasia often experience significant problems in their daily lives
and social participation. Technologies that address speech and language disorders deficit in …

Automatic recognition of aphasic speech is challenging due to various speech-language
impairments associated with aphasia as well as a scarcity of training data appropriate for …

Classifying dysarthria using neural networks is challenging due to several factors inherent to
the nature of dysarthria, the complexity of speech signals, and the requirements of effective …

This paper presents a fully automated approach for identifying speech anomalies from voice
recordings to aid in the assessment of speech impairments. By combining Connectionist …