Spaiche: Extending State-of-the-Art ASR Models to Swiss German Dialects
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Abstract (arXiv)
Recent breakthroughs in NLP largely increased the presence of ASR systems in our daily lives. However, for many low-resource languages, ASR models still need to be improved due in part to the difficulty of acquiring pertinent data. This project aims to help advance research in ASR models for Swiss German dialects, by providing insights about the performance of state-of-the-art ASR models on recently published Swiss German speech datasets. We propose a novel loss that takes into account the semantic distance between the predicted and the ground-truth labels. We outperform current state-of-the-art results by fine-tuning OpenAI's Whisper model on Swiss-German datasets.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 16 of its 26 references that are in the map. First posted on arXiv 20 Apr 2023.
Builds on
16 of 26 references.
References · 16
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4 more
- 2021SwissDial: Parallel Multidialectal Corpus of Spoken Swiss Germancited by 25
- 2022SDS-200: A Swiss German Speech to Standard German Text Corpuscited by 22
- 2020Swiss Parliaments Corpus, an Automatically Aligned Swiss German Speech to Standard German Text Corpuscited by 16
- 2022Swiss German Speech to Text system evaluationcited by 7
Built on by
Citing papers per year: 2024: 2; 2025: 5; 2026: 1.
8 papers.
- 2024Fine-tuning Whisper on Low-Resource Languages for Real-World Applicationscited by 11
- 2024Does Whisper understand Swiss German? An automatic, qualitative, and human evaluationcited by 8
- 2025A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translationcited by 7
- 2025Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languagescited by 4
- 2025Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialectscited by 2
- 2025Advancing STT for Low-Resource Real-World Speechcited by 1
- 2026Subtitle-Aligned Fine-Tuning of Whisper for Swiss German ASR: Benchmark Contamination, Convention Mismatch, and an Honest Baseline at 25.6% WER (13.8% cWER)cited by 1
- 2025SwissGPC v1.0 -- The Swiss German Podcasts Corpuscited by 0
- 2026Subtitle-Aligned Fine-Tuning of Whisper for Swiss German ASR: Benchmark Contamination, Convention Mismatch, and an Honest Baseline at 25.6% WER (13.8% cWER)29 May 2026
- 2025Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialects9 Oct 2025
- 2025SwissGPC v1.0 -- The Swiss German Podcasts Corpus24 Sep 2025
- 2025Advancing STT for Low-Resource Real-World Speech10 Jun 2025
- 2025A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation3 Jun 2025
- 2025Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languages30 Mar 2025
- 2024Fine-tuning Whisper on Low-Resource Languages for Real-World Applications20 Dec 2024
- 2024Does Whisper understand Swiss German? An automatic, qualitative, and human evaluation30 Apr 2024