Publication detail

Alzheimer's disease and automatic speech analysis: A review

PULIDO, M.L.B HERNANDEZ, J.B.A. BALLESTER, M.A.F. GONZALEZ, C.M.T. MEKYSKA, J. SMÉKAL, Z.

Original Title

Alzheimer's disease and automatic speech analysis: A review

Type

journal article in Web of Science

Language

English

Original Abstract

The objective of this paper is to present the state of-the-art relating to automatic speech and voice analysis techniques as applied to the monitoring of patients suffering from Alzheimer's disease as well as to shed light on possible future research topics. This work reviews more than 90 papers in the existing literature and focuses on the main feature extraction techniques and classification methods used. In order to guide researchers interested in working in this area, the most frequently used data repositories are also given. Likewise, it identifies the most clinically relevant results and the current lines developed in the field. Automatic speech analysis, within the Health 4.0 framework, offers the possibility of assessing these patients, without the need for a specific infrastructure, by means of non-invasive, fast and inexpensive techniques as a complement to the current diagnostic methods.

Keywords

Alzheimer's disease; automatic processing; speech; voice

Authors

PULIDO, M.L.B; HERNANDEZ, J.B.A.; BALLESTER, M.A.F.; GONZALEZ, C.M.T.; MEKYSKA, J.; SMÉKAL, Z.

Released

15. 7. 2020

ISBN

0957-4174

Periodical

EXPERT SYSTEMS WITH APPLICATIONS

Year of study

150

Number

1

State

United States of America

Pages from

1

Pages to

19

Pages count

19

URL

https://doi.org/10.1016/j.eswa.2020.113213

BibTex

@article{BUT162351,
  author="PULIDO, M.L.B and HERNANDEZ, J.B.A. and BALLESTER, M.A.F. and GONZALEZ, C.M.T. and MEKYSKA, J. and SMÉKAL, Z.",
  title="Alzheimer's disease and automatic speech analysis: A review",
  journal="EXPERT SYSTEMS WITH APPLICATIONS",
  year="2020",
  volume="150",
  number="1",
  pages="1--19",
  doi="10.1016/j.eswa.2020.113213",
  issn="0957-4174",
  url="https://doi.org/10.1016/j.eswa.2020.113213"
}