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J-GLOBAL ID：201802273678739663   Reference number：18A2041586

Phase Reconstruction from Amplitude Spectrograms Based on Von-Mises-Distribution Deep Neural Network

von-Mises分布ディープニューラルネットワークに基づく振幅スペクトログラムからの位相再構成【JST・京大機械翻訳】

Author (5)： Takamichi Shinnosuke (The University of Tokyo, Graduate School of Information Science and Technology, Japan) ,  Saito Yuki (The University of Tokyo, Graduate School of Information Science and Technology, Japan) ,  Takamune Norihiro (The University of Tokyo, Graduate School of Information Science and Technology, Japan) ,  Kitamura Daichi (The University of Tokyo, Graduate School of Information Science and Technology, Japan) ,  Saruwatari Hiroshi (The University of Tokyo, Graduate School of Information Science and Technology, Japan)
Material： IEEE Conference Proceedings  (IEEE Conf Proc)
Volume： 2018  Issue： IWAENC  Page： 286-290  Publication year： 2018 
JST Material Number： W2441A  Document type： Proceedings
Article type： 原著論文  Country of issue： United States (USA)  Language： ENGLISH (EN)

Abstract/Point： This paper presents a deep neu...

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Thesaurus term： *reconstitution ,  maximum likelihood method ,  speech signal ,  modeling ,  *phase restoration ,  artifact ,  forecast ,  *neural network (biomodel) ,  *phase (topology) ,  speech processing ,  voice quality ,  generation model ,  *spectrogram ,  *deep neural network
Semi thesaurus term： モデルパラメータ , 【Automatic Indexing@JST】

JST classification (1)： Graphic and image processing in general  (JE04010I)

Terms in the title (5)： 分布 ,  ディープニューラルネットワーク ,  振幅 ,  スペクトログラム ,  位相再構成