activity
20192026
most citedDetecting Dysfluencies in Stuttering Therapy Using wav2vec 2.0

47 citations · 143 across the 42 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

eess.AS2024★ 2 cited

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…

cs.SD2024

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…

cs.SD2024

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…

cs.CL2024

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…

cs.LG2024

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…

cs.SD2024★ 1 cited

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…

cs.CL2024★ 2 cited

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…