Datasets:

sarulab-speech
/

mls_sidon

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, Portuguese, Polish, Dutch
Format: WebDataset (.tar shards)
License: CC-BY-4.0

Dataset Structure

Each sample in the dataset contains:

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

Example (inside a .tar shard):


000001.flac
000001.meta.json
000002.flac
000002.meta.json
...

How to Use

With 🤗 Datasets

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

from datasets import load_dataset

ds = load_dataset(
    "webdataset",
    data_files="https://huggingface.co/datasets/<username>/<repo>/resolve/main/{lang}_shard-{000000..000099}.tar",
    split="train",
    streaming=True
)

for sample in ds:
    audio = sample["flac"]
    text = sample["txt"]
    print(audio, text)

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

With WebDataset (PyTorch)

import webdataset as wds

urls = "https://huggingface.co/datasets/<username>/<repo>/resolve/main/english_shard-{000000..000099}.tar"

dataset = (
    wds.WebDataset(urls)
    .decode()
    .to_tuple("flac", "txt")
)

for audio, text in dataset:
    ...

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

Original data: Multilingual LibriSpeech (MLS)