dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 22050
- name: speaker_id
dtype: string
- name: sentence_id
dtype: string
- name: duration
dtype: float64
- name: text
dtype: string
- name: split
dtype: string
splits:
- name: train
num_bytes: 1573717458
num_examples: 2373
- name: test
num_bytes: 1119588307
num_examples: 1510
- name: validation
num_bytes: 213986775
num_examples: 268
- name: held_out
num_bytes: 531217549
num_examples: 720
download_size: 2799400227
dataset_size: 3438510089
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
- split: held_out
path: data/held_out-*
authors:
- lenaso
pretty_name: Saar-Voice
Saar-Voice
A multi-speaker speech corpus for the Rhine Franconian dialect of German as spoken in Saarbrücken and the surrounding region, referred to loosely as Saarländisch.
Overview
| Property | Value |
|---|---|
| Speakers | 9 (P01–P09) |
| Total duration | ~6 hours |
| Sentences (recorded) | 4,871 |
| Sentences (unrecorded) | 3,901 |
| Sampling rate | 22,050 Hz |
| Language | Saarländisch (Rhine Franconian) |
| Format | WAV (stereo, 16-bit) |
Splits
| Split | Sentences | Purpose |
|---|---|---|
train |
2,373 | Model training |
test |
1,510 | Test set |
validation |
268 | Validation set |
held_out |
720 | Held-out speaker evaluation |
The held_out split contains recordings from speakers not seen during training, intended for further tests such as transfer learning experiments.
The dataset additionally includes unrecorded.json, a list of 3,905 sentences for which no audio was recorded, provided for completeness and for future work.
Speakers
The corpus includes 9 speakers (P01–P09) of varying age and gender, all native speakers of Saarländisch. Speaker metadata (age, gender) is not included in this release.
Text
Sentences were sourced from:
- the MASSIVE dataset (German subset) + localized into Saarländisch dialect orthography
- several books, poem and short story collections
- texts provided directly by the local author community
A detailed breakdown is available in the corresponding paper.
Usage
from datasets import load_dataset
ds = load_dataset("UdS-LSV/Saar-Voice")
# Access the training split
for example in ds["train"]:
audio = example["audio"] # dict with array, sampling_rate, path
text = example["text"] # dialect transcription
spk = example["speaker_id"] # e.g. "P01"
Citation
If you use this dataset, please cite:
@misc{oberkircher2026saarvoice,
title = {Saar-Voice: A Multi-Speaker Saarbrücken Dialect Speech Corpus},
author = {Lena S. Oberkircher and Jesujoba O. Alabi and Dietrich Klakow and Jürgen Trouvain},
year = {2026},
url = {https://arxiv.org/abs/2604.11803}
}
License
This dataset is released under CC BY 4.0.