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SDS-200: A Swiss German Speech to Standard German Text Corpus

Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)

DOI:10.63317/37dz8d89gtq4

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.

Details

Paper ID
lrec2022-main-347
Pages
pp. 3250-3256
BibKey
pluss-etal-2022-sds
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
79-10-95546-38-2
Conference
Thirteenth Language Resources and Evaluation Conference
Location
Marseille, France
Date
20 June 2022 25 June 2022

Authors

  • MP

    Michel Plüss

  • MH

    Manuela Hürlimann

  • MC

    Marc Cuny

  • AS

    Alla Stöckli

  • NK

    Nikolaos Kapotis

  • JH

    Julia Hartmann

  • MU

    Malgorzata Anna Ulasik

  • CS

    Christian Scheller

  • YS

    Yanick Schraner

  • AJ

    Amit Jain

  • JD

    Jan Deriu

  • MC

    Mark Cieliebak

  • MV

    Manfred Vogel

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