---
license: cc-by-nc-4.0
language:
  - en
---

# LibriBrain (Sherlock Holmes 1–7)

This repository contains the LibriBrain data organised by book: MEG recordings (`.h5`), event annotations (`.tsv`), and the audiobook stimulus audio (`.wav`).

## Repository structure

Data are organised into seven top-level directories:

- `Sherlock1/`
- `Sherlock2/`
- …
- `Sherlock7/`

Each `Sherlock{i}` directory contains:

- `Sherlock{i}/derivatives/events/` — event annotation files (`.tsv`)
- `Sherlock{i}/derivatives/serialised/` — MEG recordings (`.h5`)
- `Sherlock{i}/stimuli/audio/` — stimulus audio (`.wav`)

## Stimulus audio (LibriVox)

The spoken-audio stimuli are derived from **LibriVox** public-domain recordings of the first seven Sherlock Holmes books (recording versions linked below). The stimuli are provided in this repository as WAV files converted from the LibriVox downloads.

### LibriVox source URLs (recording versions)

1. https://librivox.org/a-study-in-scarlet-version-6-by-sir-arthur-conan-doyle/
2. https://librivox.org/the-sign-of-the-four-version-3-by-sir-arthur-conan-doyle/
3. https://librivox.org/the-adventures-of-sherlock-holmes-version-4-by-sir-arthur-conan-doyle/
4. https://librivox.org/the-memoirs-of-sherlock-holmes-by-sir-arthur-conan-doyle-2/
5. https://librivox.org/the-hound-of-the-baskervilles-version-4-by-sir-arthur-conan-doyle/
6. https://librivox.org/the-return-of-sherlock-holmes-by-sir-arthur-conan-doyle-2/
7. https://librivox.org/the-valley-of-fear-version-3-by-sir-arthur-conan-doyle/

### Audio format

The WAV files in this repository are:
- WAV (PCM), mono (1 channel), 22,050 Hz, 16-bit signed integer PCM

Example conversion command (SoX):

```bash
sox "INPUT_FROM_LIBRIVOX.mp3" -c 1 -r 22050 -b 16 "OUTPUT.wav"
```

### Citation

```bibtex
@article{ozdogan2025libribrain,
  author    = {Özdogan, Miran and Landau, Gilad and Elvers, Gereon and Jayalath, Dulhan and Somaiya, Pratik and Mantegna, Francesco and Woolrich, Mark and Parker Jones, Oiwi},
  title     = {{LibriBrain}: Over 50 Hours of Within-Subject {MEG} to Improve Speech Decoding Methods at Scale},
  year      = {2025},
  journal   = {NeurIPS, Datasets \& Benchmarks Track},
  url       = {https://arxiv.org/abs/2506.02098},
}
```