Datasets:
SaarAI ASR Benchmark Outputs
Raw per-utterance model outputs (transcription manifests) produced by the gsma-asr-bench runners on SaarAI/asr-leaderboard-datasets.
- files: 570
- utterances: 4615160
- languages: 7
- models: 50
Layout
data/<language_name>/<split>__<dataset_config>__<model_slug>.jsonl
index.jsonl # one record per file (language, split, model, rows, sha256, ...)
index.csv
Directories categorise by language name; the file name begins with the split name, so both can be parsed without opening the file:
from pathlib import Path
split, dataset_config, model_slug = Path(path).stem.split('__', 2)
language_name = Path(path).parent.name
Loading
from datasets import load_dataset
# everything
ds = load_dataset("SaarAI/asr-benchmark-outputs", data_files="data/**/*.jsonl", split="train")
# one language / one split
ds = load_dataset("SaarAI/asr-benchmark-outputs", data_files="data/amharic/ambient_room_noise__*.jsonl", split="train")
Row schema
audio_filepath, duration, time, text (reference), pred_text (hypothesis) plus the metadata added at upload time: model_slug, model_family, language, language_name, iso_639_3, dataset_config, split, benchmark_dataset.
Contents
| language | splits | files | utterances |
|---|---|---|---|
| amharic | ambient_room_noise, clean_studio, distant_low_volume_mic, harsh_environment, narrowband_2g_packet_loss, randomized_phone_channel, test, wideband_phone_volte | 266 | 3820160 |
| fulani | test | 34 | 54795 |
| kinyarwanda | test | 12 | 120912 |
| malagasy | test | 30 | 62445 |
| ndebele | test | 12 | 23196 |
| shona | test | 14 | 24486 |
| zulu | ambient_room_noise, clean_studio, distant_low_volume_mic, harsh_environment, narrowband_2g_packet_loss, randomized_phone_channel, test, wideband_phone_volte | 202 | 509166 |
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