1 citations · 2 across the 19 of their papers we have counts for
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When Layer Selection Misleads Speech Depression Detection
Paula A. Perez-Toro, David Gimeno-Gómez, Daniel Rückert +1
Pretrained speech representations are increasingly used for depression detection, but selecting the best encoder layer on the same data used for evaluation biases reported performa…
Do Speech Representations Preserve Regional Accent Across Read and Spontaneous Speech?
Paula A. Perez-Toro, Tomas Arias-Vergara, Annette Schwarz +4
Regional accent cues can be captured under matched conditions, but it remains unclear whether they persist between read and spontaneous speech. We study RVG1, with 500 German speak…
Beyond Decodability: Do Acoustic Factors Drive Predictions in Speech-Based Alzheimer's Assessment?
Serli Kopar, Alkis Koudounas, Roshan P. Rane +3
Speech-based Alzheimer's disease (AD) assessments increasingly rely on pretrained self-supervised learning (SSL) models that learn acoustic representations directly from raw audio,…
Child-Adapted Structured Phonological Representations for Interpretable Speech Sound Analysis
Abner Hernandez, Tomás Arias Vergara, Andreas Maier +1
Structured phonological representations provide an interpretable alternative to generic speech embeddings, but existing models are largely trained on adult speech. We adapt PhonoQ-…
Towards clinical adoption of voice and speech as measures of health: the need for harmonization
Nicholas Cummins, Vikram Ramanarayanan, Daniel Low +9
Speech and voice are multidimensional signals that capture both communicative intent and underlying physiological processes, providing a unique, non-invasive window into health. An…
PANDA - Prototype-Anchored Alignment for Partially Unpaired Multimodal Learning, with Applications to Alzheimers MRI and TCGA Pathology
Sheethal Bhat, Mahfuzur Rahman Chowdhury, Paula Andrea Perez-Toro +4
Multimodal medical prediction often faces incomplete pairing: auxiliary modalities with complementary signal are available for only a subset of subjects (or none) and cannot be ass…
A Standardized Framework for Machine Learning in Power System Protection
Julian Oelhaf, Georg Kordowich, Paula Andrea Pérez-Toro +4
Studies of machine-learning-based power-system protection increasingly report near-perfect scores, yet the meaning of those scores depends strongly on the evaluation setting. Prote…
Understanding Multilingual Medical ASR Adaptation Through Layer-Wise Analysis
Souranil Kahali, Rituparna Bose, Abner Hernandez +4
Medical automatic speech recognition (MedASR) requires adaptation to specialised terminology, limited annotated clinical data, and multilingual use cases. Although large-scale pret…
Motor, Cognitive, or Corpus? What Survives Cross-Lingual Transfer in Speech-Based Parkinsons Disease Detection
Serli Kopar, Sam Gijsen, Abner Hernandez +2
Self-supervised learning (SSL) speech representations achieve strong performance for Parkinson's disease (PD) detection within individual corpora. However, it remains unclear wheth…
Structured Phonological Representations for Audio-Articulatory rtMRI Speech Classification
Abner Hernandez, Tomás Arias Vergara, Daiqi Liu +2
Real-time MRI makes it possible to observe vocal-tract articulation during speech, but mapping these articulatory patterns to phonetic and phonological categories remains challengi…
Robustness and Stability Analysis of Differentiable Shift-Variant FBP for Cone-Beam CT under Challenging Acquisition Settings
Chengze Ye, Linda-Sophie Schneider, Yipeng Sun +5
The differentiable shift-variant filtered backprojection (SV-FBP) framework enables data-driven estimation of redundancy weights for cone-beam CT reconstruction under general sourc…
Fault Inception Detection in Real-World Disturbance Data for Power System Protection
Julian Oelhaf, Mehran Pashaei, Paula Andrea Perez-Toro +5
Large collections of real-world disturbance recordings are increasingly available in transmission networks, but their value for power system protection and automated disturbance an…
Beyond Binary: Speech Representations Across the Cognitive Score Hierarchy
Serli Kopar, Roshan Prakash Rane, Christian Mychajliw +6
This study examines the relationship between speech representations and the hierarchical structure of cognitive assessment in mild cognitive impairment. Utilizing 5,754 German neur…
Speech-Guided Multimodal Learning for Vocal Tract Segmentation in Real-Time MRI
Daiqi Liu, Lukas Mulzer, Md Hasan +11
Segmenting vocal tract articulators in real-time MRI (rtMRI) is a challenging dynamic image segmentation problem characterized by low contrast, rapid motion, and limited spatial re…
SIREM: Speech-Informed MRI Reconstruction with Learned Sampling
Md Hasan, Nyvenn Castro, Daiqi Liu +6
Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for speech science and clinical a…
Just Ask for a Table: A Thirty-Token User Prompt Defeats Sponsored Recommendations in Twelve LLMs
Andreas Maier, Jeta Sopa, Gozde Gul Sahin +2
Wu et al. (2026) showed that most frontier large language models (LLMs) recommend a sponsored, roughly twice-as-expensive flight when their system prompt contains a soft sponsorshi…
A Deep Risk Estimator for Known Operator Learning
Andreas Maier, Md Hasan, Paulina Conrad +1
We describe an approach for estimating the statistical risk of deep networks that contain a mix of learned and known operators. Building on the maximal training error bounds previo…
Multilingual Phonological Feature Recognition with Self-Supervised Speech Models
Abner Hernandez, Tomás Arias-Vergara, Daiqi Liu +2
Phonological features provide a language-general and linguistically grounded representation of speech. We present PhonoQ-2.0, a multilingual frame-level phonological feature recogn…
Bias and Fairness in Self-Supervised Acoustic Representations for Cognitive Impairment Detection
Kashaf Gulzar, Korbinian Riedhammer, Elmar Nöth +2
Speech-based detection of cognitive impairment (CI) offers a promising non-invasive approach for early diagnosis, yet performance disparities across demographic and clinical subgro…