Special Issue on Applications of Speech and Language Technologies in Healthcare-Reference-Cited by-同舟云学术

Special Issue on Applications of Speech and Language Technologies in Healthcare

Published:2023-06-05 Issue:11 Volume:13 Page:6840
ISSN:2076-3417
Container-title:Applied Sciences
language:en
Short-container-title:Applied Sciences

Author:

Hernáez-Rioja Inma¹^ORCID,Gonzalez-Lopez Jose A.²^ORCID,Christensen Heidi³

Affiliation:

1. HiTZ Center—Aholab, University of the Basque Country UPV/EHU, 48014 Bilbao, Spain

2. Department Signal Theory, Telematics and Communications, University of Granada, 18015 Granada, Spain

3. Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK

Abstract

In recent years, the exploration and uptake of digital health technologies have advanced rapidly with a real potential impact to revolutionise healthcare delivery and associated industries [...]

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Link

https://www.mdpi.com/2076-3417/13/11/6840/pdf

Reference10 articles.

1. Attas, D., Power, N., Smithies, J., Bee, C., Aadahl, V., Kellett, S., Blackmore, C., and Christensen, H. (2022). Automated Detection of the Competency of Delivering Guided Self-Help for Anxiety via Speech and Language Processing. Appl. Sci., 12.

2. Ozbolt, A.S., Moro-Velazquez, L., Lina, I., Butala, A.A., and Dehak, N. (2022). Things to Consider When Automatically Detecting Parkinson’s Disease Using the Phonation of Sustained Vowels: Analysis of Methodological Issues. Appl. Sci., 12.

3. Moreno-Torres, I., Lozano, A., Nava, E., and Bermúdez-De-Alvear, R. (2021). Which Utterance Types Are Most Suitable to Detect Hypernasality Automatically?. Appl. Sci., 11.

4. Farrús, M., Codina-Filbà, J., Reixach, E., Andrés, E., Sans, M., Garcia, N., and Vilaseca, J. (2021). Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status. Appl. Sci., 11.

5. Ezzine, K., Di Martino, J., and Frikha, M. (2022). Intelligibility Improvement of Esophageal Speech Using Sequence-to-Sequence Voice Conversion with Auditory Attention. Appl. Sci., 12.