Automatic Data-Driven Approaches for Evaluating the Phonemic Verbal Fluency Task with Healthy Adults

Hali Lindsay, Nicklas Linz, Johannes Tröger, Jan Alexandersson, Josef van Genabith, Christoph Kaller

In: 2019 3rd International Conference on Natural Language and Speech Processing (ICNLSP). International Conference on Natural Language and Speech Processing (ICNLSP-2019) 3rd September 12-13 Trento Italy IEEExplore 9/2019.


Phonemic Verbal Fluency (PVF) is a cognitive assessment task where a patient is asked to produce words constrained to a given alphabetical letter for a specified time duration. Patient productions are later evaluated based on strategies to reveal crucial diagnostic information by manually scoring results according to predetermined clinical criteria. In this paper, we propose four alternative similarity metrics and evaluate them in a two-fold argument, using the clinical criteria as a baseline. First, we consider the capacity of each metric to model PVF production using a rank-based approach, and then consider the metrics ability to compute finer resolution clinical measures that are indicative of the underlying strategy. Automation of the clinical criteria and proposed metrics are evaluated on PVF performances for16 letters from 32 healthy German students(n=512). Weighted phonemic edit distance performed best overall for modeling both production and strategy.


German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz