JeevanDai/OpenSLR54-Nepali-ASR-parquet

OpenSLR 54: Large Nepali ASR training data set (unmodified parquet repackaging)

This is an unofficial repackaging of the official OpenSLR 54 release (SLR54, https://www.openslr.org/54/), converted to parquet so it can be streamed with 🤗 datasets. It is not affiliated with or endorsed by OpenSLR or the original authors. All credit for the data belongs to the original creators (see Citation).

What's inside

• —157,905 utterances, 16 shards: one per original zip (asr_nepali_0.zip … asr_nepali_f.zip)
• —audio: the original FLAC bytes, unchanged (not re-encoded, resampled or trimmed)
• —utt_id, speaker_id (anonymized), transcription: from the official utt_spk_text.tsv
• —One train split: the original release has no train/test split

from datasets import load_dataset
ds = load_dataset("JeevanDai/OpenSLR54-Nepali-ASR-parquet", split="train", streaming=True)

Changes from the original

Only the container format: zip + TSV → parquet. Audio bytes and transcripts are as distributed by OpenSLR.

License

CC BY-SA 4.0, inherited from the original data set (https://creativecommons.org/licenses/by-sa/4.0/). You must give appropriate credit (cite the paper below) and distribute derivatives under the same license.

Citation

If you use this data, please cite the original data set:

@inproceedings{kjartansson-etal-sltu2018,
    title     = {Crowd-Sourced Speech Corpora for Javanese, Sundanese, Sinhala, Nepali, and Bangladeshi Bengali},
    author    = {Oddur Kjartansson and Supheakmungkol Sarin and Knot Pipatsrisawat and Martin Jansche and Linne Ha},
    booktitle = {Proc. 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU)},
    year      = {2018},
    address   = {Gurugram, India},
    month     = aug,
    pages     = {52--55},
    url       = {http://dx.doi.org/10.21437/SLTU.2018-11}
}

Original resource: OpenSLR SLR54, "Large Nepali ASR training data set", https://www.openslr.org/54/