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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.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…

eess.AS2022★ 2 cited

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…

eess.AS2022

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…

eess.AS2022

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…

eess.AS2022★ 1 cited

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…

eess.AS2022★ 20 cited

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…

eess.AS2022

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…