2024-03-28T22:37:52Z
https://repository.nii.ac.jp/oai
oai:repository.nii.ac.jp:02000365
2023-01-11T05:50:25Z
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NII Technical Report (NII-2017-003E):A simple RNN-plus-highway network for statistical parametric speech synthesis
Wang, Xin
高木, 信二
Takaki, Shinji
山岸, 順一
Yamagishi, Junichi
テクニカルレポート
Technical Report
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.
国立情報学研究所
2017-04-27
eng
departmental bulletin paper
https://doi.org/10.20736/0002000365
https://repository.nii.ac.jp/records/2000365
10.20736/0002000365
1346-5597
NIIテクニカル・レポート
NII Technical Report
1
8
https://repository.nii.ac.jp/record/2000365/files/17-003E.pdf
application/pdf
463 KB
2022-06-09