---
pretty_name: Bagpiper Pretraining Data Collection
language:
- en
task_categories:
- automatic-speech-recognition
- text-to-audio
tags:
- audio
- speech
- music
- sound
- multimodal
- rich-caption
- opus
size_categories:
- 100M<n<1B
---

# Bagpiper Pretraining Data Collection

**Upload in progress. This repository is not yet complete and should not be
used or cited until this notice is removed.**

Opus-compressed audio with rich captions and curation subset labels, in the
archive layout the ESPnet speechlm dataloader reads directly.

This is the compressed, directly trainable counterpart to
[espnet/Bagpiper_PreTrain_Data](https://huggingface.co/datasets/espnet/Bagpiper_PreTrain_Data),
which ships HuggingFace-style Parquet that the training code cannot load.

Planned contents: 16 kHz mono Ogg/Opus at about 32 kbps, roughly 20 TB, with
each utterance carrying its rich caption as a plain string and its membership
in the curation subsets (`speech_und`, `speech_gen`, `sound_und`, `sound_gen`,
`music_und`, `music_gen`, plus the SFT-sized variants). An utterance belongs to
zero, one or two of the base subsets.

A full dataset card, per-dataset statistics and usage instructions replace this
notice when the upload completes.