Datasets:
WAXAL Pseudo-Labels (3-model agreement)
PRIVATE working artifact for the Google WAXAL ASR Challenge — not for redistribution.
High-confidence pseudo-labels for the WAXAL unlabeled split, produced by a 3-model agreement cascade:
a clip is kept only when the fine-tuned champion (w2v-BERT-2.0 CTC) and XLS-R-300m agree
(CER ≤ 0.12), and the fine-tuned Omnilingual-ASR-300M independently confirms the champion transcript
(CER ≤ 0.22). omni is architecturally diverse (different corpus/tokenizer), so it decorrelates the
same-family champion↔XLS-R agreement. The label is the champion's transcript.
| config (lang) | pseudo-labels |
|---|---|
| lin (Lingala) | see split |
| sna (Shona) | see split |
| lug (Luganda) | see split |
Fields
id, audio (16 kHz), text (champion transcript), agree_xlsr (CER champ↔XLS-R), agree_omni
(CER champ↔omni), dur (seconds).
Provenance & license
Audio is derived from google/WaxalNLP (unlabeled split). This repo re-hosts it privately only as a
working backup; obtain the clean labeled data from google/WaxalNLP and respect its license. Contains no
Phase-1 test transcriptions.
Load
from datasets import load_dataset
ds = load_dataset("anyantudre/waxal-pseudo", "lug", split="train")
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