# SwissDial: Parallel Multidialectal Corpus of Spoken Swiss German

arXiv: https://arxiv.org/abs/2103.11401 · HTML: https://mlsanity.com/paper/2103.11401/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 26 references that are in the map.
- First posted on arXiv 21 Mar 2021.

## Builds on (most cited first, 8 of 8)

- [WaveNet: A Generative Model for Raw Audio](https://mlsanity.com/paper/1609.03499/) (2016)
- [Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://mlsanity.com/paper/1712.05884/) (2017)
- [Generalized End-to-End Loss for Speaker Verification](https://mlsanity.com/paper/1710.10467/) (2017)
- [Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis](https://mlsanity.com/paper/1806.04558/) (2018)
- [CSS10: A Collection of Single Speaker Speech Datasets for 10 Languages](https://mlsanity.com/paper/1903.11269/) (2019)
- [Machine Translation of Low-Resource Spoken Dialects: Strategies for Normalizing Swiss German](https://mlsanity.com/paper/1710.11035/) (2017)
- [Building a mixed-lingual neural TTS system with only monolingual data](https://mlsanity.com/paper/1904.06063/) (2019)
- [A Swiss German Dictionary: Variation in Speech and Writing](https://mlsanity.com/paper/2004.00139/) (2020)

## Built on by (most cited first, 26 of 26)

- [Language Model Tokenizers Introduce Unfairness Between Languages](https://mlsanity.com/paper/2305.15425/) (2023)
- [SDS-200: A Swiss German Speech to Standard German Text Corpus](https://mlsanity.com/paper/2205.09501/) (2022)
- [STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions](https://mlsanity.com/paper/2305.18855/) (2023)
- [A Survey of Corpora for Germanic Low-Resource Languages and Dialects](https://mlsanity.com/paper/2304.09805/) (2023)
- [Fine-tuning Whisper on Low-Resource Languages for Real-World Applications](https://mlsanity.com/paper/2412.15726/) (2024)
- [Assessing Evaluation Metrics for Speech-to-Speech Translation](https://mlsanity.com/paper/2110.13877/) (2021)
- [Evaluating Pixel Language Models on Non-Standardized Languages](https://mlsanity.com/paper/2412.09084/) (2024)
- [Spaiche: Extending State-of-the-Art ASR Models to Swiss German Dialects](https://mlsanity.com/paper/2304.11075/) (2023)
- [Does Whisper understand Swiss German? An automatic, qualitative, and human evaluation](https://mlsanity.com/paper/2404.19310/) (2024)
- [Swiss German Speech to Text system evaluation](https://mlsanity.com/paper/2207.00412/) (2022)
- [Dialect Transfer for Swiss German Speech Translation](https://mlsanity.com/paper/2310.09088/) (2023)
- [A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation](https://mlsanity.com/paper/2506.02894/) (2025)
- [RoDia: A New Dataset for Romanian Dialect Identification from Speech](https://mlsanity.com/paper/2309.03378/) (2023)
- [The ML-SUPERB 2.0 Challenge: Towards Inclusive ASR Benchmarking for All Language Varieties](https://mlsanity.com/paper/2509.07139/) (2025)
- [2nd Swiss German Speech to Standard German Text Shared Task at SwissText 2022](https://mlsanity.com/paper/2301.06790/) (2023)
- [Low-resource Bilingual Dialect Lexicon Induction with Large Language Models](https://mlsanity.com/paper/2304.09957/) (2023)
- [Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialects](https://mlsanity.com/paper/2510.07890/) (2025)
- [Text-to-Speech Pipeline for Swiss German -- A comparison](https://mlsanity.com/paper/2305.19750/) (2023)
- [Dialetto, ma Quanto Dialetto? Transcribing and Evaluating Dialects on a Continuum](https://mlsanity.com/paper/2410.14589/) (2024)
- [Advancing STT for Low-Resource Real-World Speech](https://mlsanity.com/paper/2506.08836/) (2025)
- [Benchmarking NLP-supported Language Sample Analysis for Swiss Children's Speech](https://mlsanity.com/paper/2504.00780/) (2025)
- [Voice Adaptation for Swiss German](https://mlsanity.com/paper/2505.22054/) (2025)
- [Swiss Parliaments Corpus Re-Imagined (SPC_R): Enhanced Transcription with RAG-based Correction and Predicted BLEU](https://mlsanity.com/paper/2506.07726/) (2025)
- [SwissGPC v1.0 -- The Swiss German Podcasts Corpus](https://mlsanity.com/paper/2509.19866/) (2025)
- [Can LLM Agents Identify Spoken Dialects like a Linguist?](https://mlsanity.com/paper/2603.29541/) (2026)
- [Dialect-Robust Speech Language Models with Synthetic Pseudo-Dialect Augmentation](https://mlsanity.com/paper/2610.09321/) (2026)

## Abstract (arXiv)

Swiss German is a dialect continuum whose natively acquired dialects significantly differ from the formal variety of the language. These dialects are mostly used for verbal communication and do not have standard orthography. This has led to a lack of annotated datasets, rendering the use of many NLP methods infeasible. In this paper, we introduce the first annotated parallel corpus of spoken Swiss German across 8 major dialects, plus a Standard German reference. Our goal has been to create and to make available a basic dataset for employing data-driven NLP applications in Swiss German. We present our data collection procedure in detail and validate the quality of our corpus by conducting experiments with the recent neural models for speech synthesis.