Presentation 2016-08-25
Pronunciation Error Detection using DNN Articulatory Model based on Transfer Learning
Richeng Duan, Tatsuya Kawahara, Masatake Dantsuji,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Aiming at detecting pronunciation errors produced by second language learners and providing corrective feedbacks related with articulation, we address effective articulatory models based on deep neural network (DNN). Articulatory attributes are defined for manner and place of articulation. In order to efficiently train these models of non-native speech without using such data, which is difficult to collect in a large scale, we propose to exploit large speech corpora of native and target language to model inter-language phenomena. We also investigate closely-related secondary tasks which aim at effective learning of DNN articulatory models. These methods are applied to Mandarin Chinese pronunciation learning by Japanese native speakers. Effects of these methods are confirmed in the native attribute classification and pronunciation error detection of non-native speech.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) CAPTPronunciation Error DetectionArticulation ModelingTransfer Learning
Paper # SP2016-39
Date of Issue 2016-08-17 (SP)

Conference Information
Committee SP
Conference Date 2016/8/24(2days)
Place (in Japanese) (See Japanese page)
Place (in English) ACCMS, Kyoto Univ.
Topics (in Japanese) (See Japanese page)
Topics (in English) Audio event processing, etc.
Chair Kazunori Mano(Shibaura Inst. of Tech.)
Vice Chair Hiroki Mori(Utsunomiya Univ.)
Secretary Hiroki Mori(Kobe Univ.)
Assistant Taichi Asami(NTT) / Kei Hashimoto(Nagoya Inst. of Tech.)

Paper Information
Registration To Technical Committee on Speech
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Pronunciation Error Detection using DNN Articulatory Model based on Transfer Learning
Sub Title (in English)
Keyword(1) CAPTPronunciation Error DetectionArticulation ModelingTransfer Learning
1st Author's Name Richeng Duan
1st Author's Affiliation Kyoto university(Kyoto Univ.)
2nd Author's Name Tatsuya Kawahara
2nd Author's Affiliation Kyoto university(Kyoto Univ.)
3rd Author's Name Masatake Dantsuji
3rd Author's Affiliation Kyoto university(Kyoto Univ.)
Date 2016-08-25
Paper # SP2016-39
Volume (vol) vol.116
Number (no) SP-189
Page pp.pp.65-70(SP),
#Pages 6
Date of Issue 2016-08-17 (SP)