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20222026
most citedThe Influence of Dataset Partitioning on Dysfluency Detection Systems

20 citations · 32 across the 17 of their papers we have counts for

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7 papers · 1 filter

cs.SD2026

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…

cs.SD2025

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…

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.SD2023★ 3 cited

Vocoder-Free Non-Parallel Conversion of Whispered Speech With Masked Cycle-Consistent Generative Adversarial Networks

Dominik Wagner, Ilja Baumann, Tobias Bocklet

Cycle-consistent generative adversarial networks have been widely used in non-parallel voice conversion (VC). Their ability to learn mappings between source and target features wit…

cs.SD2023★ 6 cited

Generative Models for Improved Naturalness, Intelligibility, and Voicing of Whispered Speech

Dominik Wagner, Sebastian P. Bayerl, Hector A. Cordourier Maruri +1

This work adapts two recent architectures of generative models and evaluates their effectiveness for the conversion of whispered speech to normal speech. We incorporate the normal…

cs.SD2022

Speaker Adaptation for End-To-End Speech Recognition Systems in Noisy Environments

Dominik Wagner, Ilja Baumann, Sebastian P. Bayerl +2

We analyze the impact of speaker adaptation in end-to-end automatic speech recognition models based on transformers and wav2vec 2.0 under different noise conditions. By including s…