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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 5 of 5  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
SP 2019-06-13
13:30
Kanagawa Tokyo Institute of Technology A study on style transplantation modeling techniques for DNN-based speech synthesis
Yoshiki Hiruta (Tokyo Tech), Tomoki Koriyama (The Univ. of Tokyo), Yuuki Tachioka (Denso IT Lab), Takao Kobayashi (Tokyo Tech) SP2019-1
This paper investigates style transplantation modeling techniques for DNN-based statistical parametric speech synthesis.... [more] SP2019-1
pp.1-6
SP, SIP, EA 2017-03-01
12:40
Okinawa Okinawa Industry Support Center [Poster Presentation] Prosodic Word Embeddings for DNN-based speech synthesis
Yusuke Ijima, Nobukatsu Hojo, Ryo Masumura, Taichi Asami (NTT) EA2016-109 SIP2016-164 SP2016-104
This paper proposed a novel word embeddings with prosodic information (prosodic word embeddings) for DNN-based speech sy... [more] EA2016-109 SIP2016-164 SP2016-104
pp.153-158
SP 2017-01-21
11:00
Tokyo The University of Tokyo [Poster Presentation] Evaluation of DNN-Based Voice Conversion Deceiving Anti-spoofing Verification
Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari (UT) SP2016-69
This paper proposes a novel training algorithm for high-quality Deep Neural Network (DNN)-based voice conversion. To imp... [more] SP2016-69
pp.29-34
SP 2017-01-21
15:35
Tokyo The University of Tokyo Conversational Speech Synthesis dealing with Sequence of Sentences
Ishin Fukuoka, Kazuhiko Iwata, Tetsunori Kobayashi (Waseda Univ.) SP2016-74
We proposed a conversational speech synthesis system that takes account of dialogue structure-based features. Convention... [more] SP2016-74
pp.59-64
SP, IPSJ-SLP, NLC, IPSJ-NL
(Joint) [detail]
2016-12-20
15:10
Tokyo NTT Musashino R&D [Poster Presentation] F0 control by modeling differential features in DNN-based speech synthesis
Shuhei Yamada, Takashi Nose, Akinori Ito (Tohoku Univ.) SP2016-55
We have been developing ``tailor-made speech synthesis,'' a framework which enables users to modify synthetic speech nat... [more] SP2016-55
pp.37-42
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