@ARTICLE{Igras-Cybulska_Magdalena_Speech_2023,
 author={Igras-Cybulska, Magdalena and Hemmerling, Daria and Ziółko, Mariusz and Datka, Wojciech and Stogowska, Ewa and Kucharski, Michał and Rzepka, Rafał and Ziółko, Bartosz},
 volume={vol. 48},
 number={No 3},
 journal={Archives of Acoustics},
 pages={289-315},
 howpublished={online},
 year={2023},
 publisher={Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics},
 abstract={The goal of this article is to present and compare recent approaches which use speech and voice analysis as biomarkers for screening tests and monitoring of some diseases. The article takes into account metabolic, respiratory, cardiovascular, endocrine, and nervous system disorders. A selection of articles was performed to identify studies that assess voice features quantitatively in selected disorders by acoustic and linguistic voice analysis. Information was extracted from each paper in order to compare various aspects of datasets, speech parameters, methods of applied analysis and obtained results. 110 research papers were reviewed and 47 databases were summarized. Speech analysis is a promising method for early diagnosis of certain disorders. Advanced computer voice analysis with machine learning algorithms combined with the widespread availability of smartphones allows diagnostic analysis to be conducted during the patient’s visit to the doctor or at the patient’s home during a telephone conversation. Speech analysis is a simple, low-cost, non-invasive and easy-toprovide method of medical diagnosis. These are remarkable advantages, but there are also disadvantages. The effectiveness of disease diagnoses varies from 65% up to 99%. For that reason it should be treated as a medical screening test and should be an indication of the need for classic medical tests.},
 type={Article},
 title={Speech Analysis as a Tool for Detection and Monitoring of Medical Conditions: A review},
 URL={http://journals.pan.pl/Content/128239/PDF-MASTER/aoa.2023.146640.pdf},
 doi={10.24425/aoa.2023.146640},
 keywords={speech analysis, speech features, acoustic parameters, linguistic analysis, voice biomarkers, screening tests},
}