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20202026
most citedCOVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings

299 citations · 574 across the 12 of their papers we have counts for

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9 papers · 1 filter

cs.SD2026

CCMAN: Cognitive Instability-Aware Cross-Modal Attention Network for Interpretable Temporal Biomarkers of Verbal Fluency Speech

Madhurananda Pahar, Caitlin Illingworth, Dorota Braun +2

Early detection of cognitive decline from speech offers a scalable and non-invasive alternative to conventional clinical assessment. Verbal fluency tasks are particularly informati…

cs.SD2026

PROCESS-2: A Benchmark Speech Corpus for Early Cognitive Impairment Detection

Madhurananda Pahar, Caitlin H. Illingworth, Bahman Mirheidari +7

Speech-based analysis offers a scalable and non-invasive approach for detecting cognitive decline, yet progress has been constrained by the limited availability of clinically valid…

cs.SD2025★ 4 cited

CognoSpeak: an automatic, remote assessment of early cognitive decline in real-world conversational speech

Madhurananda Pahar, Fuxiang Tao, Bahman Mirheidari +8

The early signs of cognitive decline are often noticeable in conversational speech, and identifying those signs is crucial in dealing with later and more serious stages of neurodeg…

cs.SD2024

Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The PROCESS Challenge

Fuxiang Tao, Bahman Mirheidari, Madhurananda Pahar +12

Dementia is associated with various cognitive impairments and typically manifests only after significant progression, making intervention at this stage often ineffective. To addres…

cs.SD2021

Wake-Cough: cough spotting and cougher identification for personalised long-term cough monitoring

Madhurananda Pahar, Marisa Klopper, Byron Reeve +4

We present `wake-cough', an application of wake-word spotting to coughs using a Resnet50 and the identification of coughers using i-vectors, for the purpose of a long-term, persona…

cs.SD2021★ 31 cited

Automatic non-invasive Cough Detection based on Accelerometer and Audio Signals

Madhurananda Pahar, Igor Miranda, Andreas Diacon +1

We present an automatic non-invasive way of detecting cough events based on both accelerometer and audio signals. The acceleration signals are captured by a smartphone firmly attac…

cs.SD2021★ 106 cited

COVID-19 Detection in Cough, Breath and Speech using Deep Transfer Learning and Bottleneck Features

Madhurananda Pahar, Marisa Klopper, Robin Warren +1

We present an experimental investigation into the effectiveness of transfer learning and bottleneck feature extraction in detecting COVID-19 from audio recordings of cough, breath…

cs.SD2021★ 83 cited

Automatic Cough Classification for Tuberculosis Screening in a Real-World Environment

Madhurananda Pahar, Marisa Klopper, Byron Reeve +3

Objective: The automatic discrimination between the coughing sounds produced by patients with tuberculosis (TB) and those produced by patients with other lung ailments. Approach: W…

cs.SD2020★ 299 cited

COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings

Madhurananda Pahar, Marisa Klopper, Robin Warren +1

We present a machine learning based COVID-19 cough classifier which can discriminate COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a smartphon…