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

arXiv: https://arxiv.org/abs/2605.14888 · HTML: https://mlsanity.com/paper/2605.14888/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 57 references that are in the map.
- First posted on arXiv 14 May 2026.

## Builds on (most cited first, 10 of 10)

- [Alzheimer's Dementia Recognition through Spontaneous Speech: The ADReSS Challenge](https://mlsanity.com/paper/2004.06833/) (2020)
- [Detecting cognitive decline using speech only: The ADReSSo Challenge](https://mlsanity.com/paper/2104.09356/) (2021)
- [Multilingual Alzheimer's Dementia Recognition through Spontaneous Speech: a Signal Processing Grand Challenge](https://mlsanity.com/paper/2301.05562/) (2023)
- [The Dem@Care Experiments and Datasets: a Technical Report](https://mlsanity.com/paper/1701.01142/) (2016)
- [Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The PROCESS Challenge](https://mlsanity.com/paper/2412.15230/) (2024)
- [CognoSpeak: an automatic, remote assessment of early cognitive decline in real-world conversational speech](https://mlsanity.com/paper/2501.05755/) (2025)
- [Predicting Cognitive Decline: A Multimodal AI Approach to Dementia Screening from Speech](https://mlsanity.com/paper/2502.08862/) (2025)
- [False positive bias in AI-powered speech-based cognitive screening for multilingual English speakers in the UK](https://mlsanity.com/paper/2602.13047/) (2026)
- [Leveraging Multimodal Methods and Spontaneous Speech for Alzheimer's Disease Identification](https://mlsanity.com/paper/2412.09928/) (2024)
- [CogPic: A Multimodal Dataset for Early Cognitive Impairment Assessment via Picture Description Tasks](https://mlsanity.com/paper/2604.01626/) (2026)

## Built on by (most cited first, 2 of 2)

- [A Multimodal Framework for Dementia Detection via Linguistic and Acoustic Representation Learning](https://mlsanity.com/paper/2605.25540/) (2026)
- [CCMAN: Cognitive Instability-Aware Cross-Modal Attention Network for Interpretable Temporal Biomarkers of Verbal Fluency Speech](https://mlsanity.com/paper/2609.14764/) (2026)

## Abstract (arXiv)

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 validated datasets collected under realistic conditions. We introduce PROCESS-2, a large-scale speech dataset designed to support research on automatic assessment of cognitive impairment from spontaneous and task-oriented speech. The dataset comprises recordings from 200 healthy controls, 150 mild cognitive impairment, and 50 dementia diagnoses collected using the CognoMemory digital assessment platform. Each participant completed a single assessment session, including picture description and verbal fluency tasks, accompanied by manually verified transcripts and participant-level metadata. PROCESS-2 contains approximately 21 hours of speech audio with predefined train/test partitions. Comprehensive technical validation evaluated demographic balance, clinical consistency, recording stability, embedding-space structure, and reproducible baseline modelling performance, demonstrating clinically meaningful group separation and stable performance across modelling approaches while preserving real-world conversational variability. PROCESS-2 is released under controlled access via Hugging Face to enable responsible reuse while protecting participant privacy, providing a reproducible benchmark resource for speech-based cognitive assessment research.