access_time 16 de dezembro de 2019 às 14:30 até 16 de dezembro de 2019 às 16:30
place Anfiteatro PA-3 (Piso -1, Pavilhão de Matemática), IST, Alameda
Brain diseases, and more specifically neurodegenerative disorders, include a range of conditions that affect the brain causing irreversible and progressive damages. There is no cure for many of these diseases, but the early detection of the symptoms onset may mitigate their progress. The initial screening is performed through the patient’s natural history. Then, depending on clinical symptoms, different additional tests and examinations may follow. These may include neuropsychological tests targeting the evaluation of cognitive functions, such as memory, planning, and language, or vocal tests assessing motor functions of speech production. In both cases, speech is used as the primary means to transmit information about ourselves and to perform the clinical evaluation. The current process to screen neurodegenerative disorders present important disadvantages, being both highly costly and time-consuming. These factors become particularly burdensome when frequent re-assessment is required to finetune dosage of drugs. For these reasons, there is an increasing need for additional, noninvasive, and cost-effective tools allowing a preliminary identification of diseases in their early clinical stages. In this context, speech and language play a fundamental role in the diagnostic process. Speech is an ecological way to collect bio-metric information, as it can be elicited and recorded automatically relatively easily, and at much lower cost than in-person clinical assessment. In this thesis, I address the challenge of using speech and language technologies to contribute to the clinical diagnosis of neurodegenerative diseases. The use of these technologies may ease the screening process of these disorders and provide clinicians with an objective, complementary diagnostic tool. According to clinical symptoms presentations, I identified three distinct areas in which this dissertation may contribute to the advance of the current state of the art: monitoring of speech, cognitive, and language abilities. With respect to these areas, I propose to: (1) Define a general and standard set of features that are able of modeling the symptoms of a disorder affecting motor production of speech, such as Parkinson’s disease. This set of features is used to assess the relevance of different speech tasks in Portuguese dedicated at evaluating phonation, respiration, and articulation. (2) Propose an on-line implementation of a representative set of neuropsychological tests used in the screening of dementia, such as Mild Cognitive Impairment, exploiting automatic speech recognition technology. To evaluate the feasibility of the monitoring tool, a Portuguese speech corpus including the recordings of 5 people diagnosed with cognitive impairments and 5 healthy control subjects was collected. (3) Develop an automatic method to analyze pragmatic aspects of discourse production, in particular to analyze topic coherence. This method is further complemented with lexical, syntactic, and semantic aspects of discourse, in order to provide a comprehensive evaluation of discourse production that is shown to be useful for the detection of Alzheimer’s disease.
local_offer Prova de Doutoramento
person Candidato: Anna Maria Pompili
supervisor_account Orientador: Prof. Alberto Abad Gareta / Prof.ª Isabel Pavão Martins