# DigiDiaDem

4 items

An Unforgettable Memory Day at Vinohrady with DigiDiaDem

June 18, 2026

DigiDiaDem Cognitive Screening Speech Technology

Concern about memory can begin a long search for someone who will connect individual examinations and recommend the right next step. At Nezapomenutelný den paměti na Vinohradech, the DigiDiaDem team used an anonymised story resembling the Czech tale of the Little Hen and the Little Rooster to show how fragmented that journey can become. The case also demonstrated how a short digital prescreening can complement a standard assessment without replacing a clinical diagnosis.

The DigiDiaDem Speech-Cognitive Dataset: Initial Experiments on Detecting Cognitive Impairments From Speech

February 6, 2026

DigiDiaDem Cognitive Screening Speech Technology Machine Learning

Speech-based research into cognitive impairment needs datasets that connect carefully designed tasks, clinical context and reproducible evaluation. Our IEEE Access article introduces the DigiDiaDem Speech-Cognitive Dataset and the first experiments built on it. The work links dialogue-system design, speech recognition, data preparation and machine-learning evaluation within one research workflow.

Detection of Cognitive Disorders Using ASR-Based Nonsense Words Repetition

August 22, 2025

DigiDiaDem Cognitive Screening Speech Technology Machine Learning

Short speech tasks can reveal cognitive changes without requiring a long clinical interview. This paper examines whether automatic speech recognition can evaluate immediate repetition of nonsense words and distinguish healthy participants from people with cognitive impairment. The experiment shows why recognition errors, phonological similarity and the choice of language model all matter when speech technology becomes part of a screening method.

Automatic Cognitive Disorder Detection through Semantic Analysis of Verbal Image Descriptions

August 22, 2025

DigiDiaDem Cognitive Screening Speech Technology Machine Learning

A spoken image description contains information about more than pronunciation: it also shows which concepts and relations a person notices and how they organise them in language. This paper combines speech recognition, formal semantic analysis and machine learning to compare Czech descriptions with an expert reference. The resulting semantic features offer an interpretable route towards scalable screening for cognitive disorders.