datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
asr_benchmark_storeclipquill-asr-benchmark
Measuring whisper-tiny vs whisper-base in a browser tab
Word error rate, wall-clock timing, transfer size and peak memory for two
quantised Whisper tiers running entirely client-side in a real Chrome window,
with the scripts that produced every number.
If you are building an in-browser transcription page, the two results worth
knowing before you pick a model tier:
On clean synthetic audio the two tiers tie. If that is all you test, you
will conclude the tier does not matter… See the full description on the dataset page: https://huggingface.co/datasets/sophia8888/clipquill-asr-benchmark.asr-benchmark-outputs
SaarAI ASR Benchmark Outputs
Raw per-utterance model outputs (transcription manifests) produced by the gsma-asr-bench runners on SaarAI/asr-leaderboard-datasets.
files: 508
utterances: 4390208
languages: 7
models: 47
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… See the full description on the dataset page: https://huggingface.co/datasets/SaarAI/asr-benchmark-outputs.indic-asr-benchmark
Indic ASR Benchmark — Nine Languages
Speech, human references, and side-by-side transcripts from multiple speech-to-text systems
across nine Indian languages — the evaluation data behind Navana's public Bodhi ASR
benchmark. Every clip comes from openly available research datasets, and every system is scored
the same way, on the same audio.
Released by Navana Tech, the team behind Bodhi, our
Indian-language speech-to-text engine.
A companion Hindi-only benchmark, with the full… See the full description on the dataset page: https://huggingface.co/datasets/Navana-AI/indic-asr-benchmark.nepali-asr-benchmark
Nepali ASR Benchmark
Per-utterance reference, hypothesis, WER, and CER for the six released Nepali ASR
checkpoints evaluated on three independent test sets. Released alongside the paper
Comparative Analysis of Multilingual Pre-trained Models for Nepali Automatic Speech
Recognition.
Contents
Field
Type
Description
utterance_id
string
stable identifier {test_set}-{index}
reference
string
NFC-normalised gold transcription (Devanagari)
hypothesis
string… See the full description on the dataset page: https://huggingface.co/datasets/sumanpaudel1997/nepali-asr-benchmark.result_v0.3_asr-fleurs-en-kg-ru-benchmarkgemma-french-asr-benchmark-resultsfrench-asr-benchmark-datasetresult_v0.1_asr-fleurs-en-kg-ru-benchmarkresult_v0.2_asr-fleurs-en-kg-ru-benchmark