A Comparison of Modeling Units in Sequence-to-Sequence Speech Recognition with the Transformer on Mandarin Chinese
Table 6: CER (%) on HKUST datasets compared to previous works.
['model', 'CER']
We can observe that the best CER 26.64% of character based model with the Transformer on HKUST datasets achieves a 13.4% relative reduction compared to the best CER of 30.79% by the deep multidimensional residual learning with 9 LSTM layers. It shows the superiority of the sequence-to-sequence attention-based model compared to the hybrid LSTM-HMM system.