Generating Mandarin and Cantonese F0 Contourswith Decision Trees and BLSTMs
Table 4: Comparison between the performance of MLP, single LSTM, single BLSTM and Additive-BLSTM. As mentioned in section 2.2, Cross-Delta refers to cross syllable delta feature, In-Delta refers to syllable internal delta feature. True durations are used.
['Model', 'Mandarin Syl Level  [BOLD] rmse corr', 'Mandarin Utt Level  [BOLD] rmse corr', 'Cantonese Syl Level  [BOLD] rmse corr', 'Cantonese Utt Level  [BOLD] rmse corr']
For MLP, single LSTM and single BLSTM, features of all the levels are concatenated together as input. And the Additive-BLSTM model with In-Delta performs the best on both Mandarin and Cantonese speech datasets. In the figure, adding the residual f0 contours on the base f0 contours can make the f0 contours rise and fall in a more natural way and also more similar to the natural contours.