KSoF: The Kassel State of Fluency Dataset – A Therapy Centered Dataset of Stuttering
16023Authors
nan
Abstract
AbstractStuttering is a complex speech disorder that negatively affects an individual’s ability to communicate effectively. Persons who stutter (PWS) often suffer considerably under the condition and seek help through therapy. Fluency shaping is a therapy approach where PWSs learn to modify their speech to help them to overcome their stutter. Mastering such speech techniques takes time and practice, even after therapy. Shortly after therapy, success is evaluated highly, but relapse rates are high. 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. Monitoring could create the ability to intervene early by detecting lapses in fluency. To the best of our knowledge, no public dataset is available that contains speech from people who underwent stuttering therapy that changed the style of speaking. This work introduces the Kassel State of Fluency (KSoF), a therapy-based dataset containing over 5500 clips of PWSs. The clips were labeled with six stuttering-related event types: blocks, prolongations, sound repetitions, word repetitions, interjections, and – specific to therapy – speech modifications. The audio was recorded during therapy sessions at the Institut der Kasseler Stottertherapie. The data will be made available for research purposes upon request.
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Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), pages 164–173 Marseille, 20-25 June 2022 © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0 164 How to be FAIR when you CARE: The DGS Corpus as a Case Study of Open Science Resources for Minority Languages Marc Schulder, Thomas Hanke Institute of German Sign Language and Communication of the Deaf University of Hamburg, Germany marc.schulder@uni-hamburg.de, thomas.hanke@uni-hamburg.de Abstract The publication of resources for minority languages requires a balance between making data open and accessible and respecting the rights and needs of its language community. The FAIR principles were introduced as a guide to good open data practices and they have since been complemented by the CARE principles for indigenous data governance. This article describes how the DGS Corpus implemented these principles and how the two sets of principles affected each other. The DGS Corpus is a large collection of recordings of members of the deaf community in Germany communicating in their primary language, German Sign Language (DGS); it was created to be both as a resource for linguistic research and as a record of the life experiences of deaf people in Germany. The corpus was designed with CARE in mind to respect and empower the language community and FAIR data publishing was used to enhance its usefulness as a scientific resource. Keywords: FAIR principles, CARE principles, Linguistic Corpus, German Sign Language 1. Introduction When creating resources relating to minority groups the aims of open science and open data must be bal- anced against the needs and rights of the minority group. The FAIR principles (Wilkinson et al., 2016) are designed as a guide to good open data practices, but do not take into account the needs of minority groups. The CARE principles (RDA International Indigenous Data Sovereignty IG, 2019) have been introduced as a complementary guide to ensuring that data is not only open, but also respects indigenous and minority group stakeholders. In many aspects CARE principles can be used to guide how FAIRness can be implemented. In other aspects, CARE helps identify how openness of data should be limited or adjusted to protect and em- power the language community. In this article we discuss how the CARE and FAIR principles have affected the creation and publication of the DGS Corpus, one of the largest signed language corpora available as of early 2022. The DGS Corpus is a collection of recordings of German Sign Language (DGS; Deutsche Gebärdensprache) as used by mem- bers of its language community. The primary stakeholders in the DGS language com- munity are members of the deaf community in Ger- many. Their life experience differs distinctly from that of the majority population in a variety of factors, such as language barriers, accessibility of public services, medical treatment and education, personal identity and deaf-centric aspects of social life. As such they are a minority group in both a cultural and linguistic con- text. Consequently, CARE principles had to be a cen- tral tenet of the …
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Labeled Text
AbstractStuttering is a complex speech disorder that negatively affects an individual’s ability to communicate effectively. Persons who stutter (PWS) often suffer considerably under the condition and seek help through therapy. Fluency shaping is a therapy approach where PWSs learn to modify their speech to help them to overcome their stutter. Mastering such speech techniques takes time and practice, even after therapy. Shortly after therapy, success is evaluated highly, but relapse rates are high. 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. Monitoring could create the ability to intervene early by detecting lapses in fluency. To the best of our knowledge, no public dataset is available that contains speech from people who underwent stuttering therapy that changed the style of speaking. This work introduces the Kassel State of Fluency (KSoF), a therapy-based dataset containing over 5500 clips of PWSs. The clips were labeled with six stuttering-related event types: blocks, prolongations, sound repetitions, word repetitions, interjections, and – specific to therapy – speech modifications. The audio was recorded during therapy sessions at the Institut der Kasseler Stottertherapie. The data will be made available for research purposes upon request.
Publication Details
- Paper ID:
- 16023
- Year:
- 2022
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan