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            <title>Proceedings of the First Workshop on Dialects in NLP — A Resource Perspective</title>
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            <namePart type="given">Antonis</namePart>
            <namePart type="family">Anastasopoulos</namePart>
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            <namePart type="given">Angela</namePart>
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    <abstract>This paper presents a developing oral resource for South Tyrolean, a German dialect spoken in Northern Italy. The dialect is ubiquitous in spoken communication but lacks a standardised orthography. In this context, strict transcription into dialect is of limited to no utility to the local community. Instead, there is a distinct and strong demand for technology capable of directly translating spoken dialect into Standard German. To address this specific need, we introduce a dynamic, incrementally growing dataset designed to fine-tune ASR models for this translation task. Our corpus aggregates diverse sources, including media and research interviews, totalling over 13 hours of aligned audio. We describe a collaborative workflow where community partners contribute audio archives in exchange for automated transcriptions, creating a virtuous cycle of data improvement. Additionally, we detail our iterative model fine-tuning strategy, data collection challenges and the resulting improvements in model performance.</abstract>
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%0 Conference Proceedings
%T South Tyrolean Dialect-to-Standard Speech Translation: A Resource
%A Franzini, Greta H.
%A Ducceschi, Luca
%Y Anastasopoulos, Antonis
%Y Markantonatou, Stella
%Y Ralli, Angela
%Y Zampieri, Marcos
%Y Bompolas, Stavros
%Y Stamou, Vivian
%S Proceedings of the First Workshop on Dialects in NLP — A Resource Perspective
%D 2026
%8 May
%I Association for Computational Linguistics
%C Palma de Mallorca
%F franzini-ducceschi-2026-south
%X This paper presents a developing oral resource for South Tyrolean, a German dialect spoken in Northern Italy. The dialect is ubiquitous in spoken communication but lacks a standardised orthography. In this context, strict transcription into dialect is of limited to no utility to the local community. Instead, there is a distinct and strong demand for technology capable of directly translating spoken dialect into Standard German. To address this specific need, we introduce a dynamic, incrementally growing dataset designed to fine-tune ASR models for this translation task. Our corpus aggregates diverse sources, including media and research interviews, totalling over 13 hours of aligned audio. We describe a collaborative workflow where community partners contribute audio archives in exchange for automated transcriptions, creating a virtuous cycle of data improvement. Additionally, we detail our iterative model fine-tuning strategy, data collection challenges and the resulting improvements in model performance.
%R 10.63317/3visgk9f8s7z
%U https://aclanthology.org/2026.dialres-1.19/
%U https://doi.org/10.63317/3visgk9f8s7z
%P 188-194

Markdown (Informal)

[South Tyrolean Dialect-to-Standard Speech Translation: A Resource](https://aclanthology.org/2026.dialres-1.19/) (Franzini & Ducceschi, DialRes 2026)

• South Tyrolean Dialect-to-Standard Speech Translation: A Resource (Franzini & Ducceschi, DialRes 2026)

ACL

• Greta H. Franzini and Luca Ducceschi. 2026. South Tyrolean Dialect-to-Standard Speech Translation: A Resource. In Proceedings of the First Workshop on Dialects in NLP — A Resource Perspective, pages 188–194, Palma de Mallorca. Association for Computational Linguistics.