SDS-200 : a Swiss German speech to Standard German text corpus

Plüss, Michel; Hürlimann, Manuela; Cuny, Marc; Stöckli, Alla; Kapotis, Nikolaos; Hartmann, Julia; Ulasik, Malgorzata Anna; Scheller, Christian; Schraner, Yanick; Jain, Amit; Deriu, Jan Milan; Cieliebak, Mark; Vogel, Manfred

doi:10.21256/zhaw-26131

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-26131

Publication type:	Conference paper
Type of review:	Peer review (publication)
Title:	SDS-200 : a Swiss German speech to Standard German text corpus
Authors:	Plüss, Michel Hürlimann, Manuela Cuny, Marc Stöckli, Alla Kapotis, Nikolaos Hartmann, Julia Ulasik, Malgorzata Anna Scheller, Christian Schraner, Yanick Jain, Amit Deriu, Jan Milan Cieliebak, Mark Vogel, Manfred
et. al:	No
DOI:	10.21256/zhaw-26131
Proceedings:	Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)
Page(s):	3250
Pages to:	3256
Conference details:	13th Language Resources and Evaluation Conference (LREC), Marseille, France, 20-25 June 2022
Issue Date:	Jun-2022
Publisher / Ed. Institution:	European Language Resources Association
Language:	English
Subjects:	Swiss German; Speech to text
Subject (DDC):	430: German
Abstract:	We present SDS-200, a corpus of Swiss German dialectal speech with Standard German text translations, annotated with dialect, age, and gender information of the speakers. The dataset allows for training speech translation, dialect recognition, and speech synthesis systems, among others. The data was collected using a web recording tool that is open to the public. Each participant was given a text in Standard German and asked to translate it to their Swiss German dialect before recording it. To increase the corpus quality, recordings were validated by other participants. The data consists of 200 hours of speech by around 4000 different speakers and covers a large part of the Swiss German dialect landscape. We release SDS-200 alongside a baseline speech translation model, which achieves a word error rate (WER) of 30.3 and a BLEU score of 53.1 on the SDS-200 test set. Furthermore, we use SDS-200 to fine-tune a pre-trained XLS-R model, achieving 21.6 WER and 64.0 BLEU.
URI:	https://aclanthology.org/2022.lrec-1.347 https://digitalcollection.zhaw.ch/handle/11475/26131
Related research data:	https://github.com/stt4sg/dialektsammlung-public https://paperswithcode.com/dataset/common-voice https://paperswithcode.com/dataset/must-c
Fulltext version:	Published version
License (according to publishing contract):	CC BY-NC 4.0: Attribution - Non commercial 4.0 International
Departement:	Applied Linguistics School of Engineering
Organisational Unit:	Centre for Artificial Intelligence (CAI) Institute of Language Competence (ILC)
Published as part of the ZHAW project:	End-to-End Low-Resource Speech Translation for Swiss German Dialects
Appears in collections:	Publikationen School of Engineering

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Plüss, M., Hürlimann, M., Cuny, M., Stöckli, A., Kapotis, N., Hartmann, J., Ulasik, M. A., Scheller, C., Schraner, Y., Jain, A., Deriu, J. M., Cieliebak, M., & Vogel, M. (2022). SDS-200 : a Swiss German speech to Standard German text corpus [Conference paper]. Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), 3250–3256. https://doi.org/10.21256/zhaw-26131

Plüss, M. et al. (2022) ‘SDS-200 : a Swiss German speech to Standard German text corpus’, in Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association, pp. 3250–3256. Available at: https://doi.org/10.21256/zhaw-26131.

M. Plüss et al., “SDS-200 : a Swiss German speech to Standard German text corpus,” in Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), Jun. 2022, pp. 3250–3256. doi: 10.21256/zhaw-26131.

PLÜSS, Michel, Manuela HÜRLIMANN, Marc CUNY, Alla STÖCKLI, Nikolaos KAPOTIS, Julia HARTMANN, Malgorzata Anna ULASIK, Christian SCHELLER, Yanick SCHRANER, Amit JAIN, Jan Milan DERIU, Mark CIELIEBAK und Manfred VOGEL, 2022. SDS-200 : a Swiss German speech to Standard German text corpus. In: Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022) [online]. Conference paper. European Language Resources Association. Juni 2022. S. 3250–3256. Verfügbar unter: https://aclanthology.org/2022.lrec-1.347

Plüss, Michel, Manuela Hürlimann, Marc Cuny, Alla Stöckli, Nikolaos Kapotis, Julia Hartmann, Malgorzata Anna Ulasik, et al. 2022. “SDS-200 : A Swiss German Speech to Standard German Text Corpus.” Conference paper. In Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), 3250–56. European Language Resources Association. https://doi.org/10.21256/zhaw-26131.

Plüss, Michel, et al. “SDS-200 : A Swiss German Speech to Standard German Text Corpus.” Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), European Language Resources Association, 2022, pp. 3250–56, https://doi.org/10.21256/zhaw-26131.