Datasets:

espnet
/

Bagpiper_SFT_Data

Each row is one complete training sequence and contains both text and encoded audio. Files are split into deterministic Parquet shards targeting about 256 MiB each.

Field	Type	Description
`row_id`	string	Globally unique `source_subset:example_id` release key
`example_id`	string	Original source identifier (not globally unique)
`partition`	string	`generation` or `understanding`
`source_subset`	string	Internal source group retained for provenance
`split`	string	Release split, initially `train`
`direction`	string	`text_to_audio` or `audio_to_text`
`messages`	list of structs	Ordered `{role, modality, content, audio_index}` messages
`audio`	struct	`{path, bytes}` for the complete encoded target/input audio in this row
`audio_sha256`	string	SHA-256 of the encoded bytes
`audio_bytes`	int64	Encoded byte length
`audio_format`	string	Container/codec suffix reported by the source file
`sample_rate`	int32	Decoded sample rate, where readable
`channels`	int16	Channel count
`num_frames`	int64	Decoded frame count
`duration_seconds`	float64	Decoded duration
`metadata_json`	string	Sanitized source annotations; no paths or usernames
`source_revision`	string	Pinned raw Hugging Face source revision
`schema_version`	string	`bagpiper-self-contained-parquet-v1`

For an audio message, content is a sanitized display filename and audio_index points to the embedded audio value. Text-message content is preserved verbatim. Private source paths and usernames are never stored.

Every selected sequence has exactly one audio object. Intended reuse of the same valid audio across multiple rows is preserved.

The audit found source-local ID collisions, so consumers should use row_id as the key. example_id is preserved for traceability.