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

arXiv: https://arxiv.org/abs/2501.05755 · HTML: https://mlsanity.com/paper/2501.05755/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 40 references that are in the map.
- First posted on arXiv 10 Jan 2025.

## Builds on (most cited first, 8 of 8)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [On the Opportunities and Risks of Foundation Models](https://mlsanity.com/paper/2108.07258/) (2021)
- [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)
- [Text-guided Foundation Model Adaptation for Pathological Image Classification](https://mlsanity.com/paper/2307.14901/) (2023)
- [COVID-19 Detection in Cough, Breath and Speech using Deep Transfer Learning and Bottleneck Features](https://mlsanity.com/paper/2104.02477/) (2021)

## Built on by (most cited first, 5 of 5)

- [False positive bias in AI-powered speech-based cognitive screening for multilingual English speakers in the UK](https://mlsanity.com/paper/2602.13047/) (2026)
- [PROCESS-2: A Benchmark Speech Corpus for Early Cognitive Impairment Detection](https://mlsanity.com/paper/2605.14888/) (2026)
- [Designing and Evaluating a Conversational Agent for Early Diagnosis of Alzheimer's Disease and Related Dementias](https://mlsanity.com/paper/2509.11478/) (2025)
- [Multilingual Cognitive Impairment Detection in the Era of Foundation Models](https://mlsanity.com/paper/2604.06758/) (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)

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 neurodegenerative diseases. Clinical detection is costly and time-consuming and although there has been recent progress in the automatic detection of speech-based cues, those systems are trained on relatively small databases, lacking detailed metadata and demographic information. This paper presents CognoSpeak and its associated data collection efforts. CognoSpeak asks memory-probing long and short-term questions and administers standard cognitive tasks such as verbal and semantic fluency and picture description using a virtual agent on a mobile or web platform. In addition, it collects multimodal data such as audio and video along with a rich set of metadata from primary and secondary care, memory clinics and remote settings like people's homes. Here, we present results from 126 subjects whose audio was manually transcribed. Several classic classifiers, as well as large language model-based classifiers, have been investigated and evaluated across the different types of prompts. We demonstrate a high level of performance; in particular, we achieved an F1-score of 0.873 using a DistilBERT model to discriminate people with cognitive impairment (dementia and people with mild cognitive impairment (MCI)) from healthy volunteers using the memory responses, fluency tasks and cookie theft picture description. CognoSpeak is an automatic, remote, low-cost, repeatable, non-invasive and less stressful alternative to existing clinical cognitive assessments.