ArticleThe Journal of the Acoustical Society of America2021
The voice of COVID-19: Acoustic correlates of infection in sustained vowels.
Article in The Journal of the Acoustical Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 45 citations in OpenAlex.
- Article
- Vocal biomarkers correlate with FEV1 variations during methacholine challenge.Clinical and translational allergy · 2025Article
- Assessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and After Exacerbation.International journal of chronic obstructive pulmonary disease · 2025Article
- SympCoughNet: symptom assisted audio-based COVID-19 detection.Frontiers in digital health · 2025Article
- Distinguish the Severity of Illness Associated with Novel Coronavirus (COVID-19) Infection via Sustained Vowel Speech Features.International journal of environmental research and public health · 2023Article
- HEAR4Health: a blueprint for making computer audition a staple of modern healthcare.Frontiers in digital health · 2023Review
- A summary of the ComParE COVID-19 challenges.Frontiers in digital health · 2023Article
- Vocal biomarker predicts fatigue in people with COVID-19: results from the prospective Predi-COVID cohort study.BMJ open · 2022Article
- Deep learning and machine learning-based voice analysis for the detection of COVID-19: A proposal and comparison of architectures.Knowledge-based systems · 2022Article
- Diagnosis of COVID-19 via acoustic analysis and artificial intelligence by monitoring breath sounds on smartphones.Journal of biomedical informatics · 2022Article
- AI-Based human audio processing for COVID-19: A comprehensive overview.Pattern recognition · 2022Article
- Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell.Frontiers in digital health · 2022Review
- Evaluating the COVID-19 Identification ResNet (CIdeR) on the INTERSPEECH COVID-19 From Audio Challenges.Frontiers in digital health · 2022Article
- DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing From Decentralized Data.Frontiers in artificial intelligence · 2022Article
- Article
- Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.The Journal of the Acoustical Society of America · 2021Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 is a global health crisis that has been affecting our daily lives throughout the past year. The symptomatology of COVID-19 is heterogeneous with a severity continuum. Many symptoms are related to pathological changes in the vocal system, leading to the assumption that COVID-19 may also affect voice production. For the first time, the present study investigates voice acoustic correlates of a COVID-19 infection based on a comprehensive acoustic parameter set. We compare 88 acoustic features extracted from recordings of the vowels /i:/, /e:/, /u:/, /o:/, and /a:/ produced by 11 symptomatic COVID-19 positive and 11 COVID-19 negative German-speaking participants. We employ the Mann-Whitney U test and calculate effect sizes to identify features with prominent group differences. The mean voiced segment length and the number of voiced segments per second yield the most important differences across all vowels indicating discontinuities in the pulmonic airstream during phonation in COVID-19 positive participants. Group differences in front vowels are additionally reflected in fundamental frequency variation and the harmonics-to-noise ratio, group differences in back vowels in statistics of the Mel-frequency cepstral coefficients and the spectral slope. Our findings represent an important proof-of-concept contribution for a potential voice-based identification of individuals infected with COVID-19.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.