47 citations · 143 across the 42 of their papers we have counts for
44 papers
Reusing Latent Speech Representations for Query-Conditioned Topic Localization in Transcripts
Steffen Freisinger, Philipp Seeberger, Thomas Ranzenberger +2
Long transcripts are costly inputs for downstream NLP systems and often contain irrelevant context. We study query-conditioned topic localization: predicting the sentence span in a…
The Spoken Wikipedia Presentation Corpus
Thomas Ranzenberger, Steffen Freisinger, Tobias Bocklet +1
We present the Spoken Wikipedia Presentation Corpus, an extension of the Spoken Wikipedia Corpora featuring LLM-generated slide decks for multimodal ASR. Slides are created from LL…
Time vs. Layer: Locating Predictive Cues for Dysarthric Speech Descriptors in wav2vec 2.0
Natalie Engert, Dominik Wagner, Korbinian Riedhammer +1
Wav2vec 2.0 (W2V2) has shown strong performance in pathological speech analysis by effectively capturing the characteristics of atypical speech. Despite its success, it remains unc…
The PARLO Dementia Corpus: A German Multi-Center Resource for Alzheimer's Disease
Franziska Braun, Christopher Witzl, Florian Hönig +3
Early and accessible detection of Alzheimer's disease (AD) remains a major challenge, as current diagnostic methods often rely on costly and invasive biomarkers. Speech and languag…
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…
Reading Between the Waves: Robust Topic Segmentation Using Inter-Sentence Audio Features
Steffen Freisinger, Philipp Seeberger, Tobias Bocklet +1
Spoken content, such as online videos and podcasts, often spans multiple topics, which makes automatic topic segmentation essential for user navigation and downstream applications.…
Towards Multi-Level Transcript Segmentation: LoRA Fine-Tuning for Table-of-Contents Generation
Steffen Freisinger, Philipp Seeberger, Thomas Ranzenberger +2
Segmenting speech transcripts into thematic sections benefits both downstream processing and users who depend on written text for accessibility. We introduce a novel approach to hi…
Shared Multi-modal Embedding Space for Face-Voice Association
Christopher Simic, Korbinian Riedhammer, Tobias Bocklet
The FAME 2026 challenge comprises two demanding tasks: training face-voice associations combined with a multilingual setting that includes testing on languages on which the model w…
On the Difficulty of Token-Level Modeling of Dysfluency and Fluency Shaping Artifacts
Kashaf Gulzar, Dominik Wagner, Sebastian P. Bayerl +3
Automatic transcription of stuttered speech remains a challenge, even for modern end-to-end (E2E) automatic speech recognition (ASR) frameworks. Dysfluencies and fluency-shaping ar…
Generalizing to Unseen Disaster Events: A Causal View
Philipp Seeberger, Steffen Freisinger, Tobias Bocklet +1
Due to the rapid growth of social media platforms, these tools have become essential for monitoring information during ongoing disaster events. However, extracting valuable insight…
Pitfalls and Limits in Automatic Dementia Assessment
Franziska Braun, Christopher Witzl, Andreas Erzigkeit +4
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…
Personalized Fine-Tuning with Controllable Synthetic Speech from LLM-Generated Transcripts for Dysarthric Speech Recognition
Dominik Wagner, Ilja Baumann, Natalie Engert +4
In this work, we present our submission to the Speech Accessibility Project challenge for dysarthric speech recognition. We integrate parameter-efficient fine-tuning with latent au…
Adapter-Based Multi-Agent AVSR Extension for Pre-Trained ASR Models
Christopher Simic, Korbinian Riedhammer, Tobias Bocklet
We present an approach to Audio-Visual Speech Recognition that builds on a pre-trained Whisper model. To infuse visual information into this audio-only model, we extend it with an…
Optimized Self-supervised Training with BEST-RQ for Speech Recognition
Ilja Baumann, Dominik Wagner, Korbinian Riedhammer +1
Self-supervised learning has been successfully used for various speech related tasks, including automatic speech recognition. BERT-based Speech pre-Training with Random-projection…
Infusing Acoustic Pause Context into Text-Based Dementia Assessment
Franziska Braun, Sebastian P. Bayerl, Florian Hönig +4
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…
Large Language Models for Dysfluency Detection in Stuttered Speech
Dominik Wagner, Sebastian P. Bayerl, Ilja Baumann +3
Accurately detecting dysfluencies in spoken language can help to improve the performance of automatic speech and language processing components and support the development of more…
Outlier Reduction with Gated Attention for Improved Post-training Quantization in Large Sequence-to-sequence Speech Foundation Models
Dominik Wagner, Ilja Baumann, Korbinian Riedhammer +1
This paper explores the improvement of post-training quantization (PTQ) after knowledge distillation in the Whisper speech foundation model family. We address the challenge of outl…
MMUTF: Multimodal Multimedia Event Argument Extraction with Unified Template Filling
Philipp Seeberger, Dominik Wagner, Korbinian Riedhammer
With the advancement of multimedia technologies, news documents and user-generated content are often represented as multiple modalities, making Multimedia Event Extraction (MEE) an…
Optimized Speculative Sampling for GPU Hardware Accelerators
Dominik Wagner, Seanie Lee, Ilja Baumann +3
In this work, we optimize speculative sampling for parallel hardware accelerators to improve sampling speed. We notice that substantial portions of the intermediate matrices necess…
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…
Multi-Query Focused Disaster Summarization via Instruction-Based Prompting
Philipp Seeberger, Korbinian Riedhammer
Automatic summarization of mass-emergency events plays a critical role in disaster management. The second edition of CrisisFACTS aims to advance disaster summarization based on mul…
Information Type Classification with Contrastive Task-Specialized Sentence Encoders
Philipp Seeberger, Tobias Bocklet, Korbinian Riedhammer
User-generated information content has become an important information source in crisis situations. However, classification models suffer from noise and event-related biases which…
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…
A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problem
Sebastian P. Bayerl, Dominik Wagner, Ilja Baumann +4
Most stuttering detection and classification research has viewed stuttering as a multi-class classification problem or a binary detection task for each dysfluency type; however, th…