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, 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.