Kassel State of Fluency - Challenge
Creators
- 1. Technische Hochschule Nürnberg
- 2. Kasseler Stottertherapie
- 3. Friedrich Alexander Universität Erlangen-Nürnberg
Description
The stuttering Kassel State of Fluency corpus KSoF-C, provided is derived from
the Kassel State of Fluency (KSoF) corpus. The original corpus fea-
tures some 5500 typical and nontypical (stuttering) 3-sec segments
from 37 German speakers with an overall duration of 4,6 hours. The
segments contain speech of persons who stutter (PWO). The record-
ings from which the segments were extracted were recorded before,
during, and after PWOs underwent stuttering therapy.
KSOF-C only features the 4601 non-ambiguously labeled segments.
The task proposed in this challenge is the classification of speech
segments as one of the 8 classes - the seven stuttering-related classes
mentioned above and an eighth “garbage” class, denoting unintelligible segments, segments containing no speech, or segments that
are negatively affected by loud background noise. The dataset is split by speaker (train, 23 spk, devel, 6 spk, test, 8 spk)
Notes
How to get the data:
- be a non-profit/ academic researcher
- fill out the EULA
- send the signed EULA back to us
The signed EULA must be sent to us before we can give you acces to the data. Please follow the instructions described on the KSoF website for this. You can find the EULA here under License or on the website.
Files
Restricted
The record is publicly accessible, but files are restricted to users with access.
Request access
If you would like to request access to these files, please fill out the form below.
You need to satisfy these conditions in order for this request to be accepted:
Please sign the EULA for the KSF-C dataset first and register your team for the ACM Multimedia 2022 Computational Paralinguistics Challenge (ComParE) challenge.
The EULA for the KSF-C dataset can be obtained from sebastian.bayerl@th-nuernberg.de.
Access will be granted upon receiving the signed EULA.
http://www.compare.openaudio.eu/2022-2/
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Additional details
References
- Bayerl, S. P.; Gerczuk, M.; Batliner, A.; Bergler, C.; Amiriparian, S.; Schuller, B.; Nöth, E.; Riedhammer, K. Classification of Stuttering – The ComParE Challenge and Beyond. Computer Speech & Language 2023, 81
- Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastian Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Stephen Roberts: "The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitos", Proceedings ACM Multimedia 2022, ACM, Lisbon, Portugal, 2022.
- Sebastian P. Bayerl, Alexander Wolff von Gudenberg, Florian Hönig, Elmar Nöth, Korbinian Riedhammer: "KSoF: The Kassel State of Fluency Dataset - A Therapy Centered Dataset of Stuttering", Proceedings LREC 2022, Marseille, France, 2022.