no code implementations • 13 Jan 2023 • Saturnino Luz, Fasih Haider, Davida Fromm, Ioulietta Lazarou, Ioannis Kompatsiaris, Brian MacWhinney
This Signal Processing Grand Challenge (SPGC) targets a difficult automatic prediction problem of societal and medical relevance, namely, the detection of Alzheimer's Dementia (AD).
no code implementations • 23 Mar 2021 • Saturnino Luz, Fasih Haider, Sofia de la Fuente, Davida Fromm, Brian MacWhinney
Building on the success of the ADReSS Challenge at Interspeech 2020, which attracted the participation of 34 teams from across the world, the ADReSSo Challenge targets three difficult automatic prediction problems of societal and medical relevance, namely: detection of Alzheimer's Dementia, inference of cognitive testing scores, and prediction of cognitive decline.
no code implementations • 14 Apr 2020 • Saturnino Luz, Fasih Haider, Sofia de la Fuente, Davida Fromm, Brian MacWhinney
ADReSS provides researchers with a benchmark speech dataset which has been acoustically pre-processed and balanced in terms of age and gender, defining two cognitive assessment tasks, namely: the Alzheimer's speech classification task and the neuropsychological score regression task.
no code implementations • LREC 2014 • Brian MacWhinney, Davida Fromm
Methods for automatic detection and interpretation of metaphors have focused on analysis and utilization of the ways in which metaphors violate selectional preferences (Martin, 2006).
no code implementations • LREC 2014 • Lori Levin, Teruko Mitamura, Brian MacWhinney, Davida Fromm, Jaime Carbonell, Weston Feely, Robert Frederking, Anatole Gershman, Carlos Ramirez
The extraction rules operate on the output of a dependency parser and identify the grammatical configurations (such as a verb with a prepositional phrase complement) that are likely to contain conventional metaphors.