SlowGuess/NAACL_2022_OCR huggingface dataset:
newstest2018	newstest2019
Joint	Orig-En	Orig-De	nt18p	Orig-En	Orig-De	nt19p
Supervised Baseline (5.2M)	41.8	46.1	34.3	12.6	38.8	30.4	11.7
Unsup (same used throughout this work)	30.1	30.9	27.1	9.6	24.6	28.5	8.8
Supervised Baseline + SupBT	43.4	43.7	41.8	12.5	37.0	39.9	12.0
+ UnsupBT	33.3	33.8	31.1	9.9	27.2	30.8	9.5
+ 50-50BT	38.0	36.4	39.0	12.9	29.4	38.3	10.0
+ SupBT_Tag	44.8	47.0	40.7	13.0	40.3	38.2	12.4
+ UnsupBT_Tag	43.3	46.9	36.9	12.9	39.1	35.0	12.2
+ 50-50BT_Tag	44.4	47.1	39.6	12.9	39.4	38.0	12.2
+ 50-50BT_TagDiff	44.4	46.8	40.1	13.0	39.9	37.9	12.4
+ 21.7M Tagged Unsup & 2.3M Sup BT	44.0	46.6	39.3	13.0	39.6	36.9	12.3
+ 17.4M Tagged Unsup & 6.6M Sup BT	44.0	46.2	40.0	13.0	40.0	37.7	12.3
+ 9.4M Tagged Unsup & 14.6M Sup BT (+MediumMix_Tag)	44.7	46.8	40.8	13.0	40.1	38.2	12.6
+ 3.1M Tagged Unsup & 20.9M Sup BT (+SmallMix_Tag)	44.8	46.8	40.8	13.2	39.8	38.8	12.5
+ 1.5M Tagged Unsup & 22.5M Sup BT	44.8	47.1	40.7	13.2	40.0	38.4	12.5
+ 680K Tagged Unsup & 23.3M Sup BT	44.4	46.4	40.7	12.9	40.0	38.1	12.4
Table 12: SacreBLEU of supervised baseline plus 24M supervised or unsupervised BTs. Systems using both use the BT selection method of §5.3 with increasing values for hyperparameter  $T$ . nt18p and nt19p are paraphrase references from Freitag et al. (2020), where small BLEU score changes can indicate tangible quality difference.