33 citations · 94 across the 13 of their papers we have counts for
13 papers
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…
Speaker- and Text-Independent Estimation of Articulatory Movements and Phoneme Alignments from Speech
Tobias Weise, Philipp Klumpp, Kubilay Can Demir +6
This paper introduces a novel combination of two tasks, previously treated separately: acoustic-to-articulatory speech inversion (AAI) and phoneme-to-articulatory (PTA) motion esti…
Towards Intelligent Speech Assistants in Operating Rooms: A Multimodal Model for Surgical Workflow Analysis
Kubilay Can Demir, Belen Lojo Rodriguez, Tobias Weise +2
To develop intelligent speech assistants and integrate them seamlessly with intra-operative decision-support frameworks, accurate and efficient surgical phase recognition is a prer…
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…
PoCaPNet: A Novel Approach for Surgical Phase Recognition Using Speech and X-Ray Images
Kubilay Can Demir, Tobias Weise, Matthias May +3
Surgical phase recognition is a challenging and necessary task for the development of context-aware intelligent systems that can support medical personnel for better patient care a…
Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages
Soroosh Tayebi Arasteh, Cristian David Rios-Urrego, Elmar Noeth +4
Parkinson's disease (PD) is a neurological disorder impacting a person's speech. Among automatic PD assessment methods, deep learning models have gained particular interest. Recent…
PoCaP Corpus: A Multimodal Dataset for Smart Operating Room Speech Assistant using Interventional Radiology Workflow Analysis
Kubilay Can Demir, Matthias May, Axel Schmid +5
This paper presents a new multimodal interventional radiology dataset, called PoCaP (Port Catheter Placement) Corpus. This corpus consists of speech and audio signals in German, X-…
Self-Supervised Speech Representations Preserve Speech Characteristics while Anonymizing Voices
Abner Hernandez, Paula Andrea Pérez-Toro, Juan Camilo Vásquez-Correa +3
Collecting speech data is an important step in training speech recognition systems and other speech-based machine learning models. However, the issue of privacy protection is an in…
The effect of speech pathology on automatic speaker verification -- a large-scale study
Soroosh Tayebi Arasteh, Tobias Weise, Maria Schuster +3
Navigating the challenges of data-driven speech processing, one of the primary hurdles is accessing reliable pathological speech data. While public datasets appear to offer solutio…
Disentangled Latent Speech Representation for Automatic Pathological Intelligibility Assessment
Tobias Weise, Philipp Klumpp, Kubilay Can Demir +5
Speech intelligibility assessment plays an important role in the therapy of patients suffering from pathological speech disorders. Automatic and objective measures are desirable to…
SliTraNet: Automatic Detection of Slide Transitions in Lecture Videos using Convolutional Neural Networks
Aline Sindel, Abner Hernandez, Seung Hee Yang +2
With the increasing number of online learning material in the web, search for specific content in lecture videos can be time consuming. Therefore, automatic slide extraction from t…
Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? -- A Case Study using Dual Energy CT Data
Andreas Maier, Seung Hee Yang, Farhad Maleki +2
In the domain of medical image processing, medical device manufacturers protect their intellectual property in many cases by shipping only compiled software, i.e. binary code which…
Known Operator Learning and Hybrid Machine Learning in Medical Imaging -- A Review of the Past, the Present, and the Future
Andreas Maier, Harald Köstler, Marco Heisig +2
In this article, we perform a review of the state-of-the-art of hybrid machine learning in medical imaging. We start with a short summary of the general developments of the past in…