no code implementations • 16 Aug 2023 • Franziska Braun, Sebastian P. Bayerl, Paula A. Pérez-Toro, Florian Hönig, Hartmut Lehfeld, Thomas Hillemacher, Elmar Nöth, Tobias Bocklet, Korbinian Riedhammer
Automated dementia screening enables early detection and intervention, reducing costs to healthcare systems and increasing quality of life for those affected.
no code implementations • 30 May 2023 • Sebastian P. Bayerl, Dominik Wagner, Ilja Baumann, Florian Hönig, Tobias Bocklet, Elmar Nöth, Korbinian Riedhammer
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, this does not match the nature of stuttering, in which one dysfluency seldom comes alone but rather co-occurs with others.
no code implementations • 28 Oct 2022 • Sebastian P. Bayerl, Dominik Wagner, Florian Hönig, Tobias Bocklet, Elmar Nöth, Korbinian Riedhammer
This work explores an approach based on a modified wav2vec 2. 0 system for end-to-end stuttering detection and classification as a multi-label problem.
no code implementations • 28 Oct 2022 • Ilja Baumann, Dominik Wagner, Franziska Braun, Sebastian P. Bayerl, Elmar Nöth, Korbinian Riedhammer, Tobias Bocklet
Recent findings show that pre-trained wav2vec 2. 0 models are reliable feature extractors for various speaker characteristics classification tasks.
no code implementations • 27 Oct 2022 • Dominik Wagner, Ilja Baumann, Franziska Braun, Sebastian P. Bayerl, Elmar Nöth, Korbinian Riedhammer, Tobias Bocklet
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 representing healthy speech.
no code implementations • 17 Sep 2022 • Gabriel Figueiredo Miller, Juan Camilo Vásquez-Correa, Juan Rafael Orozco-Arroyave, Elmar Nöth
The proposed models are able to classify the speech from Parkinson's disease patients with accuracy up to 95\%.
1 code implementation • 7 Jun 2022 • Sebastian P. Bayerl, Dominik Wagner, Elmar Nöth, Tobias Bocklet, Korbinian Riedhammer
This paper empirically investigates the influence of different data splits and splitting strategies on the performance of dysfluency detection systems.
no code implementations • 7 Apr 2022 • Sebastian P. Bayerl, Dominik Wagner, Elmar Nöth, Korbinian Riedhammer
This paper shows that fine-tuning wav2vec 2. 0 [1] for the classification of stuttering on a sizeable English corpus containing stuttered speech, in conjunction with multi-task learning, boosts the effectiveness of the general-purpose wav2vec 2. 0 features for detecting stuttering in speech; both within and across languages.
no code implementations • 4 Apr 2022 • Abner Hernandez, Paula Andrea Pérez-Toro, Elmar Nöth, Juan Rafael Orozco-Arroyave, Andreas Maier, Seung Hee Yang
Compared to using Fbank features, XLSR-based features reduced WERs by 6. 8%, 22. 0%, and 7. 0% for the UASpeech, PC-GITA, and EasyCall corpus, respectively.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 10 Mar 2022 • Sebastian P. Bayerl, Alexander Wolff von Gudenberg, Florian Hönig, Elmar Nöth, Korbinian Riedhammer
To be able to monitor speech behavior over a long time, the ability to detect stuttering events and modifications in speech could help PWSs and speech pathologists to track the level of fluency.
no code implementations • LREC 2022 • Philipp Klumpp, Tomás Arias-Vergara, Paula Andrea Pérez-Toro, Elmar Nöth, Juan Rafael Orozco-Arroyave
A Wav2Vec 2. 0 acoustic model was trained with the Common Phone to perform phonetic symbol recognition and validate the quality of the generated phonetic annotation.
no code implementations • 21 Dec 2021 • Philipp Klumpp, Tomás Arias-Vergara, Juan Camilo Vásquez-Correa, Paula Andrea Pérez-Toro, Juan Rafael Orozco-Arroyave, Anton Batliner, Elmar Nöth
As one of the most prevalent neurodegenerative disorders, Parkinson's disease (PD) has a significant impact on the fine motor skills of patients.