FLEURS Javanese + Indonesian read speech (training subset used by UHM, Lost In Transcription IN-JV)

Description

What it is. The Javanese (jv_id) and Indonesian (id_id) train splits of FLEURS (Few-shot Learning Evaluation of Universal Representations of Speech; Conneau, Ma, Khanuja, Zhang, Axelrod, Dalmia, Riesa, Rivera, Bapna, 2022), read Wikipedia sentences recorded by native speakers. Original: Hugging Face google/fleurs (https://huggingface.co/datasets/google/fleurs). Licence. CC BY 4.0 (dataset card). Attribution: Google / the FLEURS authors. This package is a re-publication of the subset we used, under the same licence. Contents. 5366 clips (19.30 h) as 16 kHz mono 16-bit FLAC under audio/<config>/, with manifest.tsv (file, duration, transcript as distributed, config). Clips longer than 30 s were excluded from training by the trainer; they are included here unchanged. Targets passed through the competition's own text normaliser at training time; the text in manifest.tsv is as distributed by the source. Context. Lost In Transcription: Indonesian-Javanese Track (Mozilla Data Collective / DrivenData, Sept–Oct 2026); prize-finalist submission id-3284 (University of Hawaii at Manoa). Published at the close of the competition to satisfy the rule that external training data be made available on the Mozilla Data Collective. Contact. Samuel Watson, University of Hawaii at Manoa — [email protected] by the University of Hawaii at Manoa team at the close of the Lost In Transcription competition to satisfy the rule that external training data be made available on the Mozilla Data Collective. The package holds the audio of the subset we trained on, a manifest (file, duration, transcript), a datasheet, the licence and SHA-256 sums of every file. The data are re-published under their original open licence with attribution to the original creators (see DATASHEET.md and LICENSE).