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Korbinian Riedhammer

5 accepted papers

2025

Adapter-Based Multi-Agent AVSR Extension for Pre-Trained ASR Models

ICASSP 2025accepted

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 AV fusion module and LoRa adapters, one of the most up-to-date adapter approaches. One advantage of adapter-based approa…

Cited by 0SourceScholar
2025

Optimized Self-supervised Training with BEST-RQ for Speech Recognition

ICASSP 2025accepted

Self-supervised learning has been successfully used for various speech related tasks, including automatic speech recognition. BERT-based Speech pre-Training with Random-projection Quantizer (BEST-RQ) has achieved state-of-the-art results in speech recognition. In this work, we further optimize the B…

Cited by 3SourceScholar
2024

MMUTF: Multimodal Multimedia Event Argument Extraction with Unified Template Filling

EMNLP 2024finding

With the advancement of multimedia technologies, news documents and user-generated content are often represented as multiple modalities, making Multimedia Event Extraction (MEE) an increasingly important challenge. However, recent MEE methods employ weak alignment strategies and data augmentation wi…

Cited by 1SourcePDFScholar
2024

Optimized Speculative Sampling for GPU Hardware Accelerators

EMNLP 2024main

In this work, we optimize speculative sampling for parallel hardware accelerators to improve sampling speed. We notice that substantial portions of the intermediate matrices necessary for speculative sampling can be computed concurrently. This allows us to distribute the workload across multiple GPU…

2023

Transferring Quantified Emotion Knowledge for the Detection of Depression in Alzheimer's Disease Using Forestnets

ICASSP 2023accepted

Progressive loss of memory is the most known symptom of Alzheimer’s Disease (AD); however, it also affects other cognitive skills and leads to depression symptoms. This paper presents a transfer learning strategy for automatically detecting AD and depression in AD patients using acoustic information…

Cited by 0SourceScholar