ArticleScientific data2023
Coswara: A respiratory sounds and symptoms dataset for remote screening of SARS-CoV-2 infection.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- Keeping Medical AI Healthy and Trustworthy: A Review of Detection and Correction Methods for System Degradation.IEEE transactions on bio-medical engineering · 2026Review
- Large Language Models for Optimizing Patient Recruitment Decisions in Voice Data Generation Projects.Laryngoscope investigative otolaryngology · 2026Article
- Beyond fingerprint and voice print: cough sequence sound for identity verification.npj health systems · 2026Article
- Multimodal Deep Learning Approaches for Lung Disease Detection: A Review.Medicina (Kaunas, Lithuania) · 2026Review
- Decoding Gender in Cough Sounds: A Transformer-Based Analysis.The Laryngoscope · 2026Article
- Article
- A Robust Deep Learning Approach for COPD Automated Detection.Sensors (Basel, Switzerland) · 2026Article
- Conversational speech for respiratory triage in primary care: a pilot study.Frontiers in medicine · 2026Article
- Accelerating Cough-Based Algorithms for Pulmonary Tuberculosis Screening: Results From the CODA TB DREAM Challenge.Open forum infectious diseases · 2025Article
- Optimizing MFCC Parameters for Breathing Phase Detection.Sensors (Basel, Switzerland) · 2025Article
- Longitudinal voice monitoring in a decentralized Bring Your Own Device trial for respiratory illness detection.NPJ digital medicine · 2025Article
- Generative AI and unstructured audio data for precision public health.npj health systems · 2025Article
- Speech-based respiratory diagnostics: A study on COVID-19 detection with machine learning.PloS one · 2025Article
- Multichannel speech enhancement for automatic speech recognition: a literature review.PeerJ. Computer science · 2025Article
- Creating an Empirical Dermatology Dataset Through Crowdsourcing With Web Search Advertisements.JAMA network open · 2024Observational
- A dataset of Solicited Cough Sound for Tuberculosis Triage Testing.Scientific data · 2024Article
- Fused Audio Instance and Representation for Respiratory Disease Detection.Sensors (Basel, Switzerland) · 2024Article
- A large-scale and PCR-referenced vocal audio dataset for COVID-19.Scientific data · 2024Article
- Solicited Cough Sound Analysis for Tuberculosis Triage Testing: The CODA TB DREAM Challenge Dataset.medRxiv : the preprint server for health sciences · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
This paper presents the Coswara dataset, a dataset containing diverse set of respiratory sounds and rich meta-data, recorded between April-2020 and February-2022 from 2635 individuals (1819 SARS-CoV-2 negative, 674 positive, and 142 recovered subjects). The respiratory sounds contained nine sound categories associated with variants of breathing, cough and speech. The rich metadata contained demographic information associated with age, gender and geographic location, as well as the health information relating to the symptoms, pre-existing respiratory ailments, comorbidity and SARS-CoV-2 test status. Our study is the first of its kind to manually annotate the audio quality of the entire dataset (amounting to 65 hours) through manual listening. The paper summarizes the data collection procedure, demographic, symptoms and audio data information. A COVID-19 classifier based on bi-directional long short-term (BLSTM) architecture, is trained and evaluated on the different population sub-groups contained in the dataset to understand the bias/fairness of the model. This enabled the analysis of the impact of gender, geographic location, date of recording, and language proficiency on the COVID-19 detection performance.
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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.