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96585d7423c51783
This dataset contains lossless FLAC chunks derived from 30 Nigerian-language, Nigerian English, and Nigerian Pidgin recordings. Access requests require manual approval by the repository owner.
Contents
- Chunks: 2,245
- Chunk audio duration: 3.656 hours
- Source transcript rows represented: 4,225
- Non-speech annotations: 553 (stored separately)
- Recordings: 30
- Audio: source-rate, source-channel-count, PCM-16 FLAC
- Timestamp source:
transcript_sbpn - Quality status: unreviewed
Chunking policy
Consecutive transcript rows are merged only when they have the same recording-local speaker label, contain no intervening non-speech annotation, have a gap of at most 2.0 seconds, and produce a chunk no longer than 40.0 seconds. A single source row longer than the maximum is retained unsplit because no internal row-level cutting point exists.
Non-speech-only rows such as <music> and <laugh> are not converted into
standalone zero-length audio. They are preserved in
manifests/non_speech_events.csv and act as hard merge boundaries.
Important limitations
- Speaker labels are anonymous and local to each recording.
Speaker 1does not identify the same person in different recordings. - The SBPN timestamps were produced by full-audio forced alignment and can contain severe alignment drift. These chunks are intended for manual review and further automated QA, not direct TTS training.
- Music, singing, overlapping speech, noise, and transcript errors have not been filtered out.
- The source recordings were compressed media; FLAC avoids another lossy generation but cannot restore information removed by the source codec.
- No license is asserted here. Users must independently confirm rights, consent, and permitted uses before training or redistribution.
Fields
The Dataset Viewer reads train/metadata.jsonl. Important fields include
file_name, text, speaker_local, recording_id, exact start/end times,
source-row indices, gap statistics, and the over_40s_unsplittable flag.
manifests/chunks.jsonl contains the same records in JSONL form, while
manifests/source_summary.csv and manifests/non_speech_events.csv provide
recording-level and event-level audit information.
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