Presentation 2017-12-21
[Poster Presentation] Development of Speaker/Environment-Dependent Acoustic Model for Non-Audible Murmur Recognition Based on DNN Adaptation
Seita Noda, Tomoki Hayashi, Tomoki Toda, Kazuya Takeda,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this research, we aim to improve the performance of non-audible murmur (NAM) recognition towards the development of silent speech interfaces. First, we apply a deep learning technique to the acoustic modeling of NAM and develop speaker-dependent acoustic models using speaker adaptive training for a deep neural network (DNN). Moreover, to improve the recognition performance under noisy conditions, we also develop the noise-dependent acoustic models using noisy NAM data generated by superimposing noise signals recorded with NAM microphone. Experimental results show that our developed speaker- and noise-dependent acoustic models are effective for significantly improving NAM recognition performance under both clean and noisy conditions and achieving recognition performance under some noisy conditions comparable to that under the clean condition.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Non-Audible Murmur recognition / acoustic model / deep learning / speaker adaptation / noise adaptation
Paper # SP2017-56
Date of Issue 2017-12-14 (SP)

Conference Information
Committee NLC / IPSJ-NL / SP / IPSJ-SLP
Conference Date 2017/12/20(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Waseda Univ. Green Computing Systems Research Organization
Topics (in Japanese) (See Japanese page)
Topics (in English) The 4th Natural Language Processing Symposium & The 19th Spoken Language Symposium
Chair Hiroshi Kanayama(IBM) / Kentaro Inui(Tohoku Univ.) / Yoichi Yamashita(Ritsumeikan Univ.) / Nobuaki Minematsu(Univ. Tokyo)
Vice Chair Takeshi Sakaki(Hottolink) / Kazutaka Shimada(Kyushu Inst. of Tech.) / / Hiroki Mori(Utsunomiya Univ.)
Secretary Takeshi Sakaki(Ryukoku Univ.) / Kazutaka Shimada(NTT) / (Osaka Univ.) / Hiroki Mori(Tokyo Inst. of Tech.) / (Mixi Co. Ltd.)
Assistant Mitsuo Yoshida(Toyohashi Univ. of Tech.) / Takeshi Kobayakawa(NICT) / / Kei Hashimoto(Nagoya Inst. of Tech.) / Satoshi Kobashikawa(NTT)

Paper Information
Registration To Technical Committee on Natural Language Understanding and Models of Communication / Special Interest Group on Natural Language / Technical Committee on Speech / Special Interest Group on Spoken Language Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Poster Presentation] Development of Speaker/Environment-Dependent Acoustic Model for Non-Audible Murmur Recognition Based on DNN Adaptation
Sub Title (in English)
Keyword(1) Non-Audible Murmur recognition
Keyword(2) acoustic model
Keyword(3) deep learning
Keyword(4) speaker adaptation
Keyword(5) noise adaptation
1st Author's Name Seita Noda
1st Author's Affiliation Nagoya University(Nagoya Univ.)
2nd Author's Name Tomoki Hayashi
2nd Author's Affiliation Nagoya University(Nagoya Univ.)
3rd Author's Name Tomoki Toda
3rd Author's Affiliation Nagoya University(Nagoya Univ.)
4th Author's Name Kazuya Takeda
4th Author's Affiliation Nagoya University(Nagoya Univ.)
Date 2017-12-21
Paper # SP2017-56
Volume (vol) vol.117
Number (no) SP-368
Page pp.pp.7-10(SP),
#Pages 4
Date of Issue 2017-12-14 (SP)