Temel Kavramlar
Leveraging entity descriptions improves Named Entity Correction in ASR.
İstatistikler
DANCER outperforms PED-NEC by a CER reduction of about 7% on AISHELL-1.
DANCER offers a more pronounced CER reduction of 46% on Homophone dataset.
NE list contained 16,168 distinct named entities.
Alıntılar
"Our approach leads to a better reduction in CER for both datasets."
"Incorporating the entity rejection mechanism may slightly decrease the NE recall rate."