STT4SG-350 : a speech corpus for all Swiss German dialect regions

Plüss, Michel; Deriu, Jan Milan; Schraner, Yanick; Paonessa, Claudio; Hartmann, Julia; Schmidt, Larissa; Scheller, Christian; Hürlimann, Manuela; Samardžic, Tanja; Vogel, Manfred; Cieliebak, Mark

doi:10.18653/v1/2023.acl-short.150

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-29062

Publication type:	Conference paper
Type of review:	Peer review (publication)
Title:	STT4SG-350 : a speech corpus for all Swiss German dialect regions
Authors:	Plüss, Michel Deriu, Jan Milan Schraner, Yanick Paonessa, Claudio Hartmann, Julia Schmidt, Larissa Scheller, Christian Hürlimann, Manuela Samardžic, Tanja Vogel, Manfred Cieliebak, Mark
et. al:	No
DOI:	10.18653/v1/2023.acl-short.150 10.21256/zhaw-29062
Proceedings:	Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Page(s):	1763
Pages to:	1772
Conference details:	61st Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 9-14 July 2023
Issue Date:	2023
Publisher / Ed. Institution:	Association for Computational Linguistics
Language:	English
Subjects:	Speech corpus; Speech-to-text; Swiss German
Subject (DDC):	410.285: Computational linguistics 430: German
Abstract:	We present STT4SG-350, a corpus of Swiss German speech, annotated with Standard German text at the sentence level. The data is collected using a web app in which the speakers are shown Standard German sentences, which they translate to Swiss German and record. We make the corpus publicly available. It contains 343 hours of speech from all dialect regions and is the largest public speech corpus for Swiss German to date. Application areas include automatic speech recognition (ASR), text-to-speech, dialect identification, and speaker recognition. Dialect information, age group, and gender of the 316 speakers are provided. Genders are equally represented and the corpus includes speakers of all ages. Roughly the same amount of speech is provided per dialect region, which makes the corpus ideally suited for experiments with speech technology for different dialects. We provide training, validation, and test splits of the data. The test set consists of the same spoken sentences for each dialect region and allows a fair evaluation of the quality of speech technologies in different dialects. We train an ASR model on the training set and achieve an average BLEU score of 74.7 on the test set. The model beats the best published BLEU scores on 2 other Swiss German ASR test sets, demonstrating the quality of the corpus.
URI:	https://digitalcollection.zhaw.ch/handle/11475/29062
Fulltext version:	Published version
License (according to publishing contract):	CC BY 4.0: Attribution 4.0 International
Departement:	School of Engineering
Organisational Unit:	Centre for Artificial Intelligence (CAI)
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., Deriu, J. M., Schraner, Y., Paonessa, C., Hartmann, J., Schmidt, L., Scheller, C., Hürlimann, M., Samardžic, T., Vogel, M., & Cieliebak, M. (2023). STT4SG-350 : a speech corpus for all Swiss German dialect regions [Conference paper]. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 1763–1772. https://doi.org/10.18653/v1/2023.acl-short.150

Plüss, M. et al. (2023) ‘STT4SG-350 : a speech corpus for all Swiss German dialect regions’, in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Association for Computational Linguistics, pp. 1763–1772. Available at: https://doi.org/10.18653/v1/2023.acl-short.150.

M. Plüss et al., “STT4SG-350 : a speech corpus for all Swiss German dialect regions,” in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023, pp. 1763–1772. doi: 10.18653/v1/2023.acl-short.150.

PLÜSS, Michel, Jan Milan DERIU, Yanick SCHRANER, Claudio PAONESSA, Julia HARTMANN, Larissa SCHMIDT, Christian SCHELLER, Manuela HÜRLIMANN, Tanja SAMARDŽIC, Manfred VOGEL und Mark CIELIEBAK, 2023. STT4SG-350 : a speech corpus for all Swiss German dialect regions. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Conference paper. Association for Computational Linguistics. 2023. S. 1763–1772

Plüss, Michel, Jan Milan Deriu, Yanick Schraner, Claudio Paonessa, Julia Hartmann, Larissa Schmidt, Christian Scheller, et al. 2023. “STT4SG-350 : A Speech Corpus for All Swiss German Dialect Regions.” Conference paper. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 1763–72. Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.acl-short.150.

Plüss, Michel, et al. “STT4SG-350 : A Speech Corpus for All Swiss German Dialect Regions.” Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Association for Computational Linguistics, 2023, pp. 1763–72, https://doi.org/10.18653/v1/2023.acl-short.150.