Going Beyond the Cookie Theft Picture Test: Detecting Cognitive Impairments Using Acoustic Features
Braun F, Erzigkeit A, Lehfeld H, Hillemacher T, Riedhammer K, Bayerl SP (2022)
Publication Type: Conference contribution
Publication year: 2022
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 13502 LNAI
Pages Range: 437-448
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Brno
ISBN: 9783031162695
DOI: 10.1007/978-3-031-16270-1_36
Abstract
Standardized tests play a crucial role in the detection of cognitive impairment. Previous work demonstrated that automatic detection of cognitive impairment is possible using audio data from a standardized picture description task. The presented study goes beyond that, evaluating our methods on data taken from two standardized neuropsychological tests, namely the German SKT and a German version of the CERAD-NB, and a semi-structured clinical interview between a patient and a psychologist. For the tests, we focus on speech recordings of three sub-tests: reading numbers (SKT 3), interference (SKT 7), and verbal fluency (CERAD-NB 1). We show that acoustic features from standardized tests can be used to reliably discriminate cognitively impaired individuals from non-impaired ones. Furthermore, we provide evidence that even features extracted from random speech samples of the interview can be a discriminator of cognitive impairment. In our baseline experiments, we use OpenSMILE features and Support Vector Machine classifiers. In an improved setup, we show that using wav2vec 2.0 features instead, we can achieve an accuracy of up to 85%.
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Germany (DE)How to cite
APA:
Braun, F., Erzigkeit, A., Lehfeld, H., Hillemacher, T., Riedhammer, K., & Bayerl, S.P. (2022). Going Beyond the Cookie Theft Picture Test: Detecting Cognitive Impairments Using Acoustic Features. In Petr Sojka, Aleš Horák, Ivan Kopeček, Karel Pala (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 437-448). Brno, CZ: Springer Science and Business Media Deutschland GmbH.
MLA:
Braun, Franziska, et al. "Going Beyond the Cookie Theft Picture Test: Detecting Cognitive Impairments Using Acoustic Features." Proceedings of the 25th International Conference on Text, Speech, and Dialogue, TSD 2022, Brno Ed. Petr Sojka, Aleš Horák, Ivan Kopeček, Karel Pala, Springer Science and Business Media Deutschland GmbH, 2022. 437-448.
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