Presentation | 2021-03-03 [招待講演]空間モデルを考慮した深層学習ベースの音源分離 Masahito Togami, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, deep learning based speech source separation has been evolved rapidly. A neural network (NN) is usually learned independently of a spatial model. However, a research question remains whether the NN that is trained such as configuration is really optimal when speech source separation is performed with the spatial model. In this talk, I will introduce conventional statistical model based speech source separation and deep learning based speech source separation. After that, I will introduce four research directions which incorporate a spatial model into the NN structure, i.e. 1) Loss function of the NN that considers the spatial model, 2)Insertion of speech source separation with the spatial model into the NN structure, 3) A NN framework which estimates parameters for speech source separation with a direction-of-arrival attractor, and 4) Unsupervised learning of NN which utilizes statistical model based speech source separation as a pseudo clean signal generator. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | spatial model / speech source separation / deep learning / unsupervised learning |
Paper # | EA2020-64,SIP2020-95,SP2020-29 |
Date of Issue | 2021-02-24 (EA, SIP, SP) |
Conference Information | |
Committee | EA / US / SP / SIP / IPSJ-SLP |
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Conference Date | 2021/3/3(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Online |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | Speech, Engineering/Electro Acoustics, Signal Processing, Ultrasonics, and Related Topics |
Chair | Kenichi Furuya(Oita Univ.) / Hikaru Miura(Nihon Univ.) / Hisashi Kawai(NICT) / Kazunori Hayashi(Kyoto Univ.) / 北岡 教英(豊橋技科大) |
Vice Chair | Yoshinobu Kajikawa(Kansai Univ.) / Kentaro Matsui(NHK) / Jun Kondo(Shizuoka Univ.) / Yoshikazu Koike(Shibaura Inst. of Tech.) / / Yukihiro Bandou(NTT) / Toshihisa Tanaka(Tokyo Univ. Agri.&Tech.) |
Secretary | Yoshinobu Kajikawa(Univ. of Tokyo) / Kentaro Matsui(NTT) / Jun Kondo(Doshisha Univ.) / Yoshikazu Koike(Tohoku Univ.) / (Univ. of Tokyo) / Yukihiro Bandou(Waseda Univ.) / Toshihisa Tanaka(Hosei Univ.) / (Waseda Univ.) |
Assistant | Yukou Wakabayashi(Tokyo Metropolitan Univ.) / Tatsuya Komatsu(LINE) / Shinnosuke Hirata(Tokyo Inst. of Tech.) / Yusuke Ijima(NTT) / Yuichi Tanaka(Tokyo Univ. Agri.&Tech.) |
Paper Information | |
Registration To | Technical Committee on Engineering Acoustics / Technical Committee on Ultrasonics / Technical Committee on Speech / Technical Committee on Signal Processing / Special Interest Group on Spoken Language Processing |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | |
Sub Title (in English) | |
Keyword(1) | spatial model |
Keyword(2) | speech source separation |
Keyword(3) | deep learning |
Keyword(4) | unsupervised learning |
1st Author's Name | Masahito Togami |
1st Author's Affiliation | LINE(LINE) |
Date | 2021-03-03 |
Paper # | EA2020-64,SIP2020-95,SP2020-29 |
Volume (vol) | vol.120 |
Number (no) | EA-397,SIP-398,SP-399 |
Page | pp.pp.27-32(EA), pp.27-32(SIP), pp.27-32(SP), |
#Pages | 6 |
Date of Issue | 2021-02-24 (EA, SIP, SP) |