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sarulab-speech/mls_sidon

MLS-Sidon Overview This dataset is a cleansed version of Multilingual LibriSpeech (MLS) with Sidon speech restoration mode for Speech Synthesis and Spoken Language Modeling. The dataset is provided in WebDataset format for efficient large-scale training. Source: Multilingual LibriSpeech Languages: English, German, French, Spanish, Italian, Polish, Dutch, Portuguese Format: WebDataset (.tar shards) License: CC-BY-4.0 Dataset Structure Each… See the full description on the dataset page: https://huggingface.co/datasets/sarulab-speech/mls_sidon.

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MLS-Sidon

Overview

This dataset is a cleansed version of Multilingual LibriSpeech (MLS) with Sidon speech restoration mode for Speech Synthesis and Spoken Language Modeling.

The dataset is provided in [WebDataset](https://github.com/webdataset/webdataset) format for efficient large-scale training.

  • —Source: Multilingual LibriSpeech
  • —Languages: English, German, French, Spanish, Italian, Polish, Dutch, Portuguese
  • —Format: WebDataset (.tar shards)
  • —License: CC-BY-4.0

Dataset Structure

Each sample in the dataset contains:

  • —`flac` — audio file (48 kHz, single channel)
  • —`metadata.json` (optional) — metadata including language, speaker ID, and original MLS reference

Example (inside a .tar shard): 


000001.flac
000001.metadata.json
000002.flac
000002.metadata.json
...

How to Use

With 🤗 Datasets

You can load the WebDataset directly with Hugging Face’s datasets library:

python
import datasets
from IPython.display import Audio
from huggingface_hub import hf_hub_download
import yaml

base_url = "https://huggingface.co/datasets/sarulab-speech/mls_sidon/resolve/main/"
language = 'english'
split = 'test'
data_file_path = hf_hub_download(repo_id="sarulab-speech/mls_sidon", repo_type="dataset", filename="paths.yaml")
paths = yaml.load(open(data_file_path, "r"), Loader=yaml.FullLoader)

ds = datasets.load_dataset("webdataset", data_files=[base_url + p for p in paths['english'][split]],streaming=True)['train']

sample = next(iter(ds))
audio = sample['flac']
print(sample['metadata.json'])
Audio(audio['array'], rate=audio['sampling_rate'])

Replace language with the language (e.g., english, german).

Citation

If you use this dataset, please cite Sidon and the original MLS paper:

@misc{nakata2025sidonfastrobustopensource,
      title={Sidon: Fast and Robust Open-Source Multilingual Speech Restoration for Large-scale Dataset Cleansing}, 
      author={Wataru Nakata and Yuki Saito and Yota Ueda and Hiroshi Saruwatari},
      year={2025},
      eprint={2509.17052},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2509.17052}, 
}
@inproceedings{pratap2020mls,
  title     = {MLS: A Large-Scale Multilingual Dataset for Speech Research},
  author    = {Pratap, Vineel and Xu, Qiantong and Sriram, Anuroop and others},
  booktitle = {Interspeech},
  year      = {2020}
}

License

This dataset is released under CC-BY-4.0.

Acknowledgements