Before revision:  In order to address these issues, we propose a practical neural text-to-speech system, named Triple M, consisting of a seq2seq model with multi-guidance attention and a multi-band multi-time LPCNet.
After revision:  In order to address these issues, we propose a practical neural text-to-speech system, named Triple M, consisting of a seq2seq model with multi-guidance attention which obtains stable feature generation and robust long sentence synthesis ability by learning from the guidance attention mechanisms. Multi-guidance attention improves the robustness and naturalness of long sentence synthesis without any in-domain performance loss or online service modification. Compared with the our best result obtained by using single attention mechanism (GMM-based attention), the word error rate of long sentence synthesis decreases by 23.5\% when multi-guidance attention mechanism is applied. 2) A efficient multi-band multi-time LPCNet.