TY - CHAP A1 - Braun, Franziska A1 - Bayerl, Sebastian A1 - Hönig, Florian A1 - Lehfeld, Hartmut A1 - Hillemacher, Thomas A1 - Bocklet, Tobias A1 - Riedhammer, Korbinian T1 - Infusing Acoustic Pause Context into Text-Based Dementia Assessment N2 - Speech pauses, alongside content and structure, offer a valuable and non-invasive biomarker for detecting dementia. This work investigates the use of pause-enriched transcripts in transformer-based language models to differentiate the cognitive states of subjects with no cognitive impairment, mild cognitive impairment, and Alzheimer’s dementia based on their speech from a clinical assessment. We address three binary classification tasks: Onset, monitoring, and dementia exclusion. The performance is evaluated through experiments on a German Verbal Fluency Test and a Picture Description Test, comparing the model’s effectiveness across different speech production contexts. Starting from a textual baseline, we investigate the effect of incorporation of pause information and acoustic context. We show the test should be chosen depending on the task, and similarly, lexical pause information and acoustic cross-attention contribute differently. KW - speech biomarkers KW - dementia assessment KW - neuropsychological tests KW - pathological speech Y1 - 2024 U6 - https://doi.org/10.21437/Interspeech.2024-2496 SN - 2958-1796 ER - TY - CHAP A1 - Scheuerer, Ralph A1 - Haderlein, Tino A1 - Nöth, Elmar A1 - Bocklet, Tobias T1 - Applying X-Vectors on Pathological Speech After Larynx Removal T2 - 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) N2 - Speaker embeddings extracted from time delayed neural networks (TDNNs) contributed to major recent advancements in speaker recognition and verification. We use an X-Vector system trained on augmented VoxCeleb1 and VoxCeleb2 data to obtain embeddings for pathological speech after total or partial larynx removal. We show that our model is able to effectively distinguish and visualize patient groups when generating embeddings. We further compare various regression models on the task of automatically predicting different perceptual ratings by speech therapists (intelligibility, vocal effort, and overall quality) based on the extracted speaker embeddings. For both patient groups we show Pearson correlations in the range of +0.8; we find that Random Forest and Support Vector Regression produce scores that best resemble the experts' assessments. KW - laryngectomy KW - intelligibility KW - pathological speech KW - x-vectors Y1 - 2021 SN - 978-1-6654-3739-4 U6 - https://doi.org/10.1109/asru51503.2021.9688278 VL - 2021 SP - 1079 EP - 1086 PB - IEEE ER - TY - CHAP A1 - Braun, Franziska A1 - Witzl, Christopher A1 - Erzigkeit, Andreas A1 - Lehfeld, Hartmut A1 - Hillemacher, Thomas A1 - Bocklet, Tobias A1 - Riedhammer, Korbinian T1 - Pitfalls and Limits in Automatic Dementia Assessment T2 - Interspeech 2025 N2 - Current work on speech-based dementia assessment focuses on either feature extraction to predict assessment scales, or on the automation of existing test procedures. Most research uses public data unquestioningly and rarely performs a detailed error analysis, focusing primarily on numerical performance. We perform an in-depth analysis of an automated standardized dementia assessment, the Syndrom-Kurz-Test. We find that while there is a high overall correlation with human annotators, due to certain artifacts, we observe high correlations for the severely impaired individuals, which is less true for the healthy or mildly impaired ones. Speech production decreases with cognitive decline, leading to overoptimistic correlations when test scoring relies on word naming. Depending on the test design, fallback handling introduces further biases that favor certain groups. These pitfalls remain independent of group distributions in datasets and require differentiated analysis of target groups. KW - dementia screening KW - neuropsychological tests KW - pathological speech Y1 - 2025 U6 - https://doi.org/10.21437/Interspeech.2025-2280 SN - 2958-1796 SP - 5663 EP - 5667 PB - ISCA ER -