My Account Log in

1 option

Automatic Assessment of Parkinsonian Speech : First Workshop, AAPS 2019, Cambridge, Massachussets, USA, September 20-21, 2019, Revised Selected Papers / edited by Juan I. Godino-Llorente.

SpringerLink Books Computer Science (2011-2024) Available online

View online
Format:
Book
Contributor:
Godino-Llorente, Juan I., Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Communications in computer and information science 1865-0937 ; 1295
Communications in Computer and Information Science, 1865-0937 ; 1295
Language:
English
Subjects (All):
Artificial intelligence.
Computer engineering.
Computer networks.
Computer vision.
Social sciences-Data processing.
Artificial Intelligence.
Computer Engineering and Networks.
Computer Vision.
Computer Application in Social and Behavioral Sciences.
Computer Communication Networks.
Local Subjects:
Artificial Intelligence.
Computer Engineering and Networks.
Computer Vision.
Computer Application in Social and Behavioral Sciences.
Computer Communication Networks.
Physical Description:
1 online resource (IX, 125 pages) : 6 illustrations
Edition:
1st ed. 2020.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2020.
System Details:
text file PDF
Summary:
This book constitutes the revised and extended papers of the First Automatic Assessment of Parkinsonian Speech Workshop, AAPS 2019, held in Cambridge, Massachusetts, USA, in September 2019. The 6 full papers were thoroughly reviewed and selected from 15 submissions. They present recent research on the automatic assessment of parkinsonian speech from the point of view of such disciplines as machine learning, speech technology, phonetics, neurology, and speech therapy.
Contents:
Acoustic Analysis and Voice Quality in Parkinson Disease
Sources of Intraspeaker Variation in Parkinsonian Speech related to Speaking Style
Review of the prosodic aspect of speech for the automatic detection and assessment of Parkinson's disease
Automatic processing of aerodynamic parameters in parkinsonian dysarthria
Approaches to evaluate parkinsonian speech using artificial models
Predicting UPDRS scores in Parkinson's disease using voice signals: a deep learning/transfer-learning-based approach.
Other Format:
Printed edition:
ISBN:
978-3-030-65654-6
9783030656546
Access Restriction:
Restricted for use by site license.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account