Abstract / Description of output
While a number of studies have investigated speech and language features for the detection of AD and mild cognitive impairment and proposed various signal processing and machine learning methods for this task, the field still lacks balanced benchmark data against which different approaches can be systematically compared. This Research Topic addresses this issue by exploring the use of speech characteristics for AD recognition using balanced data and shared tasks, such as those provided by the ADReSS Challenges. These tasks have brought together groups working on this active area of research, providing the community with benchmarks for comparison of speech and language approaches to cognitive assessment. The studies in this Research Topic represent the state of the art in dementia detection, and contribute to the increasing body of evidence supporting machine learning and spoken language for detecting cognitive decline.
Original language | English |
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Pages (from-to) | 1-4 |
Number of pages | 4 |
Journal | Frontiers in Computer Science |
Volume | 3:780169 |
DOIs | |
Publication status | Published - 21 Oct 2021 |