18 citations · 51 across the 12 of their papers we have counts for
14 papers
A Systematic Evaluation of Machine Learning Methods for Fault Detection and Line Identification in Electrical Power Grids
Julian Oelhaf, Georg Kordowich, Paula Andrea Pérez-Toro +4
The integration of renewable energy sources into the electrical grid introduces complex challenges in fault detection and coordination of grid recovery mechanisms. Traditional rela…
Adapting Self-Supervised Speech Representations for Cross-lingual Dysarthria Detection in Parkinson's Disease
Abner Hernandez, Eunjung Yeo, Kwanghee Choi +12
The limited availability of dysarthric speech data makes cross-lingual detection an important but challenging problem. A key difficulty is that speech representations often encode…
LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation
Mohammad Robaitul Islam Bhuiyan, Sheethal Bhat, Melika Qahqaie +4
Precise localization and delineation of brain tumors using magnetic resonance imaging (MRI) are essential for planning therapy and guiding surgical decisions. To address this, we p…
SpeechCT-CLIP: Distilling Text-Image Knowledge to Speech for Voice-Native Multimodal CT Analysis
Lukas Buess, Jan Geier, David Bani-Harouni +6
Spoken communication plays a central role in clinical workflows. In radiology, for example, most reports are created through dictation. Yet, nearly all medical AI systems rely excl…
Impact of Data Sparsity on Machine Learning for Fault Detection in Power System Protection
Julian Oelhaf, Georg Kordowich, Changhun Kim +4
Germany's transition to a renewable energy-based power system is reshaping grid operations, requiring advanced monitoring and control to manage decentralized generation. Machine le…
Perceptual implications of automatic anonymization in pathological speech
Soroosh Tayebi Arasteh, Saba Afza, Tri-Thien Nguyen +11
Automatic anonymization is increasingly used to enable ethical sharing of clinical speech, yet its perceptual and clinical consequences remain undercharacterized. We present a huma…
A Speech-to-Video Synthesis Approach Using Spatio-Temporal Diffusion for Vocal Tract MRI
Paula Andrea Pérez-Toro, Tomás Arias-Vergara, Fangxu Xing +9
Understanding the relationship between vocal tract motion during speech and the resulting acoustic signal is crucial for aided clinical assessment and developing personalized treat…
Differential privacy enables fair and accurate AI-based analysis of speech disorders while protecting patient data
Soroosh Tayebi Arasteh, Mahshad Lotfinia, Paula Andrea Perez-Toro +6
Speech pathology has impacts on communication abilities and quality of life. While deep learning-based models have shown potential in diagnosing these disorders, the use of sensiti…
The Impact of Speech Anonymization on Pathology and Its Limits
Soroosh Tayebi Arasteh, Tomas Arias-Vergara, Paula Andrea Perez-Toro +6
Integration of speech into healthcare has intensified privacy concerns due to its potential as a non-invasive biomarker containing individual biometric information. In response, sp…
A Survey of Music Generation in the Context of Interaction
Ismael Agchar, Ilja Baumann, Franziska Braun +4
In recent years, machine learning, and in particular generative adversarial neural networks (GANs) and attention-based neural networks (transformers), have been successfully used t…
Classifying Dementia in the Presence of Depression: A Cross-Corpus Study
Franziska Braun, Sebastian P. Bayerl, Paula A. Pérez-Toro +6
Automated dementia screening enables early detection and intervention, reducing costs to healthcare systems and increasing quality of life for those affected. Depression has shared…
Cross-lingual Self-Supervised Speech Representations for Improved Dysarthric Speech Recognition
Abner Hernandez, Paula Andrea Pérez-Toro, Elmar Nöth +3
State-of-the-art automatic speech recognition (ASR) systems perform well on healthy speech. However, the performance on impaired speech still remains an issue. The current study ex…
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling
Philipp Klumpp, Tomás Arias-Vergara, Paula Andrea Pérez-Toro +2
Current state of the art acoustic models can easily comprise more than 100 million parameters. This growing complexity demands larger training datasets to maintain a decent general…
The Phonetic Footprint of Parkinson's Disease
Philipp Klumpp, Tomás Arias-Vergara, Juan Camilo Vásquez-Correa +4
As one of the most prevalent neurodegenerative disorders, Parkinson's disease (PD) has a significant impact on the fine motor skills of patients. The complex interplay of different…