| Split | # Sent | # Token src. | # Token tgt. |
|---|---|---|---|
| Train | 1.2 M | 23.7 M | 25.0 M |
| Dev | 5.000 | 84.5 K | 92.9 K |
| Test | 2.000 | 58.9 K | - |
| System | Method | P | R | F0.5 |
|---|---|---|---|---|
| YouDao (Kai et. al. 2018) | 35.24 | 18.64 | 29.91 | |
| AliGM (Zhou et. al. 2018) | 41.00 | 13.75 | 29.36 | |
| BLCU (Ren et. al. 2018) | 47.63 | 12.56 | 30.57 | |
| PKU (Zhao et. al. 2020) | 44.36 | 22.18 | 36.97 | |
| CASIA | CSeq2Edit | 43.98 | 22.65 | 37.01 |
| test set | # sent | # chars | # spelling erros (chars) | character set | genre |
|---|---|---|---|---|---|
| SIGHAN 2015 | 1,100 | 33,711 | 715 | traditional | second-language learning |
| SIGHAN 2014 | 1,062 | 53,114 | 792 | traditional | second-language learning |
| SIGHAN 2013 | 2,000 | 143,039 | 1,641 | traditional | second-language learning |
| training set | # sent | # chars | # spelling erros (chars) | character set | genre |
|---|---|---|---|---|---|
| SIGHAN 2015 | 3,174 | 95,220 | 4,237 | traditional | second-language learning |
| SIGHAN 2014 | 6,526 | 324,342 | 10,087 | traditional | second-language learning |
| SIGHAN 2013 | 350 | 17,220 | 350 | traditional | second-language learning |
| corpus | # sent | # chars | # spelling erros (chars) | character set | genre |
|---|---|---|---|---|---|
| Synthetic training dataset (Wang et. al. 2018) | 271,329 | 12M | 382,702 | simplified | news |
| System | False Positive Rate | Detection Accuracy | Detection Precision | Detection Recall | Detection F1 | Correction Accuracy | Correction Precision | Correction Recall | Correction F1 |
|---|---|---|---|---|---|---|---|---|---|
| CAS (Zhang et. al. 2015) | 11.6 | 70.1 | 80.3 | 53.3 | 64.0 | 69.2 | 79.7 | 51.5 | 62.5 |
| FASPell(Hong et. al. 2019) | - | 74.2 | 67.6 | 60.0 | 63.5 | 73.7 | 66.6 | 59.1 | 62.6 |
| Confusion-set(Wang et. al. 2019) | - | - | 66.8 | 73.1 | 69.8 | - | 71.5 | 59.5 | 64.9 |
| Soft-Masked BERT(Zhang et. al. 2020) | - | 80.9 | 73.7 | 73.2 | 73.5 | 77.4 | 66.7 | 66.2 | 66.4 |