20 citations · 32 across the 17 of their papers we have counts for
8 papers · 1 filter
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…
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…
Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem
Sebastian P. Bayerl, Dominik Wagner, Florian Hönig +3
Specially adapted speech recognition models are necessary to handle stuttered speech. For these to be used in a targeted manner, stuttered speech must be reliably detected. Recent…
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…
The Influence of Dataset Partitioning on Dysfluency Detection Systems
Sebastian P. Bayerl, Dominik Wagner, Elmar Nöth +2
This paper empirically investigates the influence of different data splits and splitting strategies on the performance of dysfluency detection systems. For this, we perform experim…
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…