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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
SP 2017-01-21
11:00		 Tokyo The University of Tokyo [Poster Presentation] A Study on Singer-Independent Singing Voice Conversion Using Read Speech Based on Neural Network
Harunori Koike, Takashi Nose, Akinori Ito (Tohoku Univ.) SP2016-67		 There is a problem that the conventional method requires the speech of the source speaker for training. We proposed a me... [more] SP2016-67
pp.17-22
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
EA, SP, SIP 2016-03-28
13:15		 Oita Beppu International Convention Center B-ConPlaza [Poster Presentation] An evaluation of F0 transformation for statistical singing voice conversion based on spectral differential filtering
Kazuhiro Kobayashi (NAIST), Tomoki Toda (Nagoya Univ./NAIST), Satoshi Nakamura (NAIST) EA2015-84 SIP2015-133 SP2015-112		 In this report, we propose a technique for cross-gender statistical singing voice conversion (SVC) with direct waveform ... [more] EA2015-84 SIP2015-133 SP2015-112
pp.105-110
SP 2015-10-15
13:25		 Hyogo Kobe Univ. Statistical singing voice conversion based on direct waveform modification and its parameter generation algorithms
Kazuhiro Kobayashi, Tomoki Toda, Satoshi Nakamura (NAIST) SP2015-60		 This report presents a novel statistical singing voice conversion (SVC) technique with direct waveform modification base... [more] SP2015-60
pp.7-12
SP 2015-10-15
13:50		 Hyogo Kobe Univ. A Study on Speaker-Independent Voice Conversion Using Spectral Differential Filter Based on Neural Network
Harunori Koike, Takashi Nose (Tohoku Univ.), Takahiro Shinozaki (Tokyo Tech), Akinori Ito (Tohoku Univ.) SP2015-61		 In this paper, we propose a novel technique for making the speech individuality of an arbitrary source (input) speaker. ... [more] SP2015-61
pp.13-18
 Results 1 - 5 of 5  /   
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