3 citations · 5 across the 14 of their papers we have counts for
14 papers
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…
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…
Digital Operating Mode Classification of Real-World Amateur Radio Transmissions
Maximilian Bundscherer, Thomas H. Schmitt, Ilja Baumann +1
This study presents an ML approach for classifying digital radio operating modes evaluated on real-world transmissions. We generated 98 different parameterized radio signals from 1…
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…
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…
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…
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…
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…
Influence of Utterance and Speaker Characteristics on the Classification of Children with Cleft Lip and Palate
Ilja Baumann, Dominik Wagner, Franziska Braun +4
Recent findings show that pre-trained wav2vec 2.0 models are reliable feature extractors for various speaker characteristics classification tasks. We show that latent representatio…
Multi-class Detection of Pathological Speech with Latent Features: How does it perform on unseen data?
Dominik Wagner, Ilja Baumann, Franziska Braun +4
The detection of pathologies from speech features is usually defined as a binary classification task with one class representing a specific pathology and the other class representi…
Nonwords Pronunciation Classification in Language Development Tests for Preschool Children
Ilja Baumann, Dominik Wagner, Sebastian Bayerl +1
This work aims to automatically evaluate whether the language development of children is age-appropriate. Validated speech and language tests are used for this purpose to test the…
Detecting Vocal Fatigue with Neural Embeddings
Sebastian P. Bayerl, Dominik Wagner, Ilja Baumann +2
Vocal fatigue refers to the feeling of tiredness and weakness of voice due to extended utilization. This paper investigates the effectiveness of neural embeddings for the detection…