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Committee Date Time Place Paper Title / Authors Abstract Paper #
SP, IPSJ-SLP, EA, SIP [detail] 2023-03-01
11:00		 Okinawa
(Primary: On-site, Secondary: Online)		 Analysis of Noisy-target Training for DNN-based speech enhancement and investigation towards its practical use
Takuya Fujimura, Tomoki Toda (Nagoya Univ.) EA2022-112 SIP2022-156 SP2022-76		 Deep neural network (DNN)-based speech enhancement usually uses a clean speech as a training target. However, it is hard... [more] EA2022-112 SIP2022-156 SP2022-76
pp.221-226
EA 2022-05-13
16:25		 Online Online Study on noise reduction with a single noisy speech based on Double-DIP
Hien Oonaka (NITTC), Takuya Fujimura (Nagoya Univ.), Ryoichi Miyazaki (NITTC) EA2022-12		 This paper proposes a new noise reduction method with an untrained Deep Neural Network ( DNN) for a single noisy speech.... [more] EA2022-12
pp.54-61
SIS 2020-12-01
11:25		 Online Online [Tutorial Lecture] A Theory for Controlling Musical Noise Based on Higher-Order Statistics
Ryoichi Miyazaki, Takuya Fujimura (NITTC) SIS2020-30		 Although nonlinear speech enhancement methods can significantly eliminate background noise, it is known to generate musi... [more] SIS2020-30
pp.18-23
EA 2019-12-12
14:00		 Fukuoka Kyushu Inst. Tech. Removal of musical noise using deep learning without pre-training
Takuya Fujimura, Ryoichi Miyazaki (NITTC) EA2019-69		 In this paper, we propose the musical noise elimination using the deep learning which does not require pre-training. It ... [more] EA2019-69
pp.23-29
AP, MW
(Joint)		 2018-09-20
14:55		 Tokyo Tokyo Tech 300 GHz, 100 Gb/s wireless transceiver based on InP-HEMT technology
Hiroshi Hamada (NTT), Takuya Fujimura, Ibrahim Abdo, Kenichi Okada (Tokyo Tech), Takuya Tsutsumi, Ho-jin Song, Hiroki Sugiyama, Hideaki Matsuzaki, Hideyuki Nosaka (NTT) MW2018-60		 These days, wireless systems which can support the data rate of 100 Gb/s are being researched for the next generation of... [more] MW2018-60
pp.7-12
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