NII Technical Reports
National Institute of Informatics
| Title | A simple RNN-plus-highway network for statistical parametric speech synthesis |
| Authors | Xin Wang, Shinji Takaki, Junichi Yamagishi |
| Abstract | In this report, we proposes a neural network structure that combines a recurrent neural network (RNN) and a deep highway network. Compared with the highway RNN structures proposed in other studies, the one proposed in this study is simpler since it only concatenates a highway network after a pre-trained RNN. The main idea is to use the ‘iterative unrolled estimation’ of a highway network to finely change the output from the RNN. The experiments on the proposed network structure with a baseline RNN and 7 highway blocks demonstrated that this network performed relatively better than a deep RNN network with a similar mode size. Furthermore, it took less than half the training time of the deep RNN. |
| Language | English |
| Published | April 27, 2017 |
| Pages | 8p |
| PDF File | 17-003E.pdf |