bambara-audio-y

Bambara speech paired with the French source line it renders, a written Bambara translation of that line, and a machine transcription of the audio. 58,447 rows, 36.66 hours, 48.77 GB of Parquet.

Load

The config is default and the splits are not_combined and combined — there is no train split, so a bare load_dataset returns a DatasetDict keyed by those two names.

from datasets import load_dataset

short = load_dataset("djelia/bambara-audio-y", split="not_combined")
long_form = load_dataset("djelia/bambara-audio-y", split="combined")
print(short[0]["fr"], short[0]["translation"], short[0]["prediction"], sep="\n")

Stream rather than pulling 48.77 GB:

stream = load_dataset("djelia/bambara-audio-y", split="not_combined", streaming=True)
for row in stream.take(5):
    print(row["path"], round(row["duration"], 2), row["translation"])

Splits

Split	Rows	Audio	Mean / median clip	Range
not_combined	53,133	36.66 h	2.48 s / 1.91 s	0.18–94.36 s
combined	5,314	36.66 h	24.84 s / 25.57 s	1.07–94.36 s

combined concatenates consecutive not_combined segments into longer clips, roughly 7–10 segments each.

Fields

Field	Description
audio	48 kHz stereo, 16-bit PCM WAV
fr	The French source line, subtitle-styled
translation	A written Bambara translation of fr
prediction	A machine transcription of the audio
duration	Seconds
path	Original relative path; encodes recording group and segmentation

Notes

The two splits hold the same 36.66 hours of speech at two segmentations — pick one, and do not split train/test across them. There is no held-out split; build your own, respecting the data/<n> recording groups in path.

translation follows the French text while prediction follows the spoken audio, so the two are different Bambara renderings of the same line and are not interchangeable as an ASR target.

Audio is 48 kHz stereo; most speech models want 16 kHz mono:

from datasets import Audio

short = short.cast_column("audio", Audio(sampling_rate=16000, mono=True))

djelia/bambara-asr-dataset-y holds the same audio without the translation and prediction columns.