Paper Abstract and Keywords |
Presentation |
2020-03-03 09:00
[Poster Presentation]
Automatic estimation of prosodic control made in English utterances using DNN-based acoustic models trained with prosodic features and labels Yang Shen, Shintarou Ando, Nobuaki Minematsu, Daisuke Saito (UTokyo), Satoshi Kobashikawa (NTT) EA2019-136 SIP2019-138 SP2019-85 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This paper investigate how to utilize DNN acoustic models trained with prosodic features and labels to detect prosodic error in Japanese English. There are four models trained with/without prosodic features or labels. Posteriorgram-based DTW difference between incomprehensible L2 speech and native speech is computed for each model. By comparing differences from baseline model trained without prosody and models trained with prosody, it is possible to detect prosodic error in L2 speech. The result showed that adding stressed vowels to output phoneme labels can help detect prosodic error. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Japanese English / prosody error / prosody feature / prosody label / DNN model / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 441, SP2019-85, pp. 201-206, March 2020. |
Paper # |
SP2019-85 |
Date of Issue |
2020-02-24 (EA, SIP, SP) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Download PDF |
EA2019-136 SIP2019-138 SP2019-85 |
Conference Information |
Committee |
SP EA SIP |
Conference Date |
2020-03-02 - 2020-03-03 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Okinawa Industry Support Center |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
SP |
Conference Code |
2020-03-SP-EA-SIP |
Language |
English (Japanese title is available) |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Automatic estimation of prosodic control made in English utterances using DNN-based acoustic models trained with prosodic features and labels |
Sub Title (in English) |
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Keyword(1) |
Japanese English |
Keyword(2) |
prosody error |
Keyword(3) |
prosody feature |
Keyword(4) |
prosody label |
Keyword(5) |
DNN model |
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1st Author's Name |
Yang Shen |
1st Author's Affiliation |
The University of Tokyo (UTokyo) |
2nd Author's Name |
Shintarou Ando |
2nd Author's Affiliation |
The University of Tokyo (UTokyo) |
3rd Author's Name |
Nobuaki Minematsu |
3rd Author's Affiliation |
The University of Tokyo (UTokyo) |
4th Author's Name |
Daisuke Saito |
4th Author's Affiliation |
The University of Tokyo (UTokyo) |
5th Author's Name |
Satoshi Kobashikawa |
5th Author's Affiliation |
Nippon Telegraph and Telephone Corporation (NTT) |
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Speaker |
Author-1 |
Date Time |
2020-03-03 09:00:00 |
Presentation Time |
90 minutes |
Registration for |
SP |
Paper # |
EA2019-136, SIP2019-138, SP2019-85 |
Volume (vol) |
vol.119 |
Number (no) |
no.439(EA), no.440(SIP), no.441(SP) |
Page |
pp.201-206 |
#Pages |
6 |
Date of Issue |
2020-02-24 (EA, SIP, SP) |
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