Presentation 2019-03-15
[Poster Presentation] Design and Evaluation of Ladder Denoising Autoencoder for Auditory Speech Feature Extraction of Overlapped Speech Separation
Hiroshi Sekiguchi, Yoshiaki Narusue, Hiroyuki Morikawa,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Primates and mammalian distinguish overlapped speech sounds from one another by recognizing a single sound source whether temporal contour of auditory speech features in auditory neurons are similar.This is called as temporal synchronization detection and clustering function. The performance of this detection and clustering function depends on the former function that is auditory speech feature extraction. The feature extraction is needed to satisfy two requirements: 1) auditory speech features are mutually stochastic independent and 2) the feature extraction should allow various complicated sounds to be represented, which leads to non-linearity.This paper introduces non-linear sparse encoder decoder model as computational model, implements it with a ladder network, and finally evaluate that network behavior. We show that our trained network can output auditory speech features that are mutually stochastic independent.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Ladder Network / Speech Separation / Auditory Neuroscience / Auditory Speech Feature Extraction / stochastic independence
Paper # EA2018-155,SIP2018-161,SP2018-117
Date of Issue 2019-03-07 (EA, SIP, SP)

Conference Information
Committee EA / SIP / SP
Conference Date 2019/3/14(2days)
Place (in Japanese) (See Japanese page)
Place (in English) i+Land nagasaki (Nagasaki-shi)
Topics (in Japanese) (See Japanese page)
Topics (in English) Engineering/Electro Acoustics, Signal Processing, Speech, and Related Topics
Chair Suehiro Shimauchi(Kanazawa Inst. of Tech.) / Shogo Muramatsu(Niigata Univ.) / Yoichi Yamashita(Ritsumeikan Univ.)
Vice Chair Kenichi Furuya(Oita Univ.) / Kanji Watanabe(Akita Pref. Univ.) / Naoyuki Aikawa(TUS) / Kazunori Hayashi(Osaka City Univ) / Akinobu Ri(Nagoya Inst. of Tech.)
Secretary Kenichi Furuya(Shizuoka Inst. of Science and Tech.) / Kanji Watanabe(NHK) / Naoyuki Aikawa(Takushoku Univ.) / Kazunori Hayashi(Hiroshima Univ.) / Akinobu Ri(Kyoto Univ.)
Assistant Keisuke Imoto(Ritsumeikan Univ.) / Daisuke Morikawa(Toyama Pref Univ.) / Katsumi Konishi(Hosei Univ.) / hyihsin(Takushoku Univ.) / Tomoki Koriyama(Tokyo Inst. of Tech.) / Satoshi Kobashikawa(NTT)

Paper Information
Registration To Technical Committee on Engineering Acoustics / Technical Committee on Signal Processing / Technical Committee on Speech
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Poster Presentation] Design and Evaluation of Ladder Denoising Autoencoder for Auditory Speech Feature Extraction of Overlapped Speech Separation
Sub Title (in English)
Keyword(1) Ladder Network
Keyword(2) Speech Separation
Keyword(3) Auditory Neuroscience
Keyword(4) Auditory Speech Feature Extraction
Keyword(5) stochastic independence
1st Author's Name Hiroshi Sekiguchi
1st Author's Affiliation The University of Tokyo(Univ. of Tokyo)
2nd Author's Name Yoshiaki Narusue
2nd Author's Affiliation The University of Tokyo(Univ. of Tokyo)
3rd Author's Name Hiroyuki Morikawa
3rd Author's Affiliation The University of Tokyo(Univ. of Tokyo)
Date 2019-03-15
Paper # EA2018-155,SIP2018-161,SP2018-117
Volume (vol) vol.118
Number (no) EA-495,SIP-496,SP-497
Page pp.pp.329-333(EA), pp.329-333(SIP), pp.329-333(SP),
#Pages 5
Date of Issue 2019-03-07 (EA, SIP, SP)