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  1. NIIテクニカル・レポート

NII Technical Report (NII-2017-003E):A simple RNN-plus-highway network for statistical parametric speech synthesis

https://doi.org/10.20736/0002000365
https://doi.org/10.20736/0002000365
af246352-a0fa-42da-9699-05e9179aa636
名前 / ファイル ライセンス アクション
17-003E.pdf NII Technical Report (NII-2017-003E):A simple RNN-plus-highway network for statistical parametric speech synthesis (463 KB)
Item type レポート / Report(1)
公開日 2022-06-09
タイトル
言語 en
タイトル NII Technical Report (NII-2017-003E):A simple RNN-plus-highway network for statistical parametric speech synthesis
言語
言語 eng
キーワード
言語 ja
主題Scheme Other
主題 テクニカルレポート
キーワード
言語 en
主題Scheme Other
主題 Technical Report
資源タイプ
資源 http://purl.org/coar/resource_type/c_6501
タイプ departmental bulletin paper
ID登録
ID登録 10.20736/0002000365
ID登録タイプ JaLC
著者 Wang, Xin

× Wang, Xin

en Wang, Xin

Search repository
高木, 信二

× 高木, 信二

ja 高木, 信二

en Takaki, Shinji

Search repository
山岸, 順一

× 山岸, 順一

ja 山岸, 順一

en Yamagishi, Junichi

Search repository
抄録
内容記述タイプ Abstract
内容記述 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.
言語 en
書誌情報 ja : NIIテクニカル・レポート
en : NII Technical Report

p. 1-8, 発行日 2017-04-27
出版者
言語 ja
出版者 国立情報学研究所
ISSN
収録物識別子タイプ ISSN
収録物識別子 1346-5597
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