g2pM: A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Dataset
Table 6: Test set accuracy of Chinese g2p systems
['[BOLD] System', '[BOLD] Test Accuracy']
Results Our model slightly underperforms Chinese BERT and outperforms all the other systems by large margin. That our simple neural model shows comparable performance to the heavy BERT model, which has more than 102M parameters, tells us two things. One is that our model is simple but powerful enough. Another is that it is not too simple for the naïve majority vote to beat.