# Detecting COPD Through Speech Analysis: A Dataset of Danish Speech and Machine Learning Approach

arXiv: https://arxiv.org/abs/2508.02354 · HTML: https://mlsanity.com/paper/2508.02354/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 42 references that are in the map.
- First posted on arXiv 4 Aug 2025.

## Builds on (most cited first, 4 of 4)

- [ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification](https://mlsanity.com/paper/2005.07143/) (2020)
- [SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives](https://mlsanity.com/paper/1407.0202/) (2014)
- [How to Compliment a Human -- Designing Affective and Well-being Promoting Conversational Things](https://mlsanity.com/paper/2302.00984/) (2023)
- [Sustained Vowels for Pre- vs Post-Treatment COPD Classification](https://mlsanity.com/paper/2406.06355/) (2024)

## Built on by (most cited first, 1 of 1)

- [Separating Voice from Age in COPD Screening](https://mlsanity.com/paper/2608.21599/) (2026)

## Abstract (arXiv)

Chronic Obstructive Pulmonary Disease (COPD) is a serious and debilitating disease affecting millions around the world. Its early detection using non-invasive means could enable preventive interventions that improve quality of life and patient outcomes, with speech recently shown to be a valuable biomarker. Yet, its validity across different linguistic groups remains to be seen. To that end, audio data were collected from 96 Danish participants conducting three speech tasks (reading, coughing, sustained vowels). Half of the participants were diagnosed with different levels of COPD and the other half formed a healthy control group. Subsequently, we investigated different baseline models using openSMILE features and learnt x-vector embeddings. We obtained a best accuracy of 67% using openSMILE features and logistic regression. Our findings support the potential of speech-based analysis as a non-invasive, remote, and scalable screening tool as part of future COPD healthcare solutions.