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    <abstract>In this study we compare two approaches (neural machine translation and edit-based) and the use of synthetic data for the task of translating normalised Swiss German ASR output into correct written Standard German for subtitles, with a special focus on syntactic differences. Results suggest that NMT is better suited to this task and that relatively simple rule-based generation of training data could be a valuable approach for cases where little training data is available and transformations are simple.</abstract>
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%0 Conference Proceedings
%T Producing Standard German Subtitles for Swiss German TV Content
%A Gerlach, Johanna
%A Mutal, Jonathan
%A Pierrette, Bouillon
%Y Ebling, Sarah
%Y Prud’hommeaux, Emily
%Y Vaidyanathan, Preethi
%S Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F gerlach-etal-2022-producing
%X In this study we compare two approaches (neural machine translation and edit-based) and the use of synthetic data for the task of translating normalised Swiss German ASR output into correct written Standard German for subtitles, with a special focus on syntactic differences. Results suggest that NMT is better suited to this task and that relatively simple rule-based generation of training data could be a valuable approach for cases where little training data is available and transformations are simple.
%R 10.18653/v1/2022.slpat-1.5
%U https://aclanthology.org/2022.slpat-1.5
%U https://doi.org/10.18653/v1/2022.slpat-1.5
%P 37-43

Markdown (Informal)

[Producing Standard German Subtitles for Swiss German TV Content](https://aclanthology.org/2022.slpat-1.5) (Gerlach et al., SLPAT 2022)

• Producing Standard German Subtitles for Swiss German TV Content (Gerlach et al., SLPAT 2022)

ACL

• Johanna Gerlach, Jonathan Mutal, and Bouillon Pierrette. 2022. Producing Standard German Subtitles for Swiss German TV Content. In Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022), pages 37–43, Dublin, Ireland. Association for Computational Linguistics.