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Paper Abstract and Keywords
Presentation 2019-03-15 10:50
Likability Estimation Model Training of Call-center Agents Based on Annotators' Skills
Hosana Kamiyama, Atsushi Ando, Ryo Masumura, Satoshi Kobashikawa, Yushi Aono (NTT) EA2018-132 SIP2018-138 SP2018-94
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a new technique for estimating the likability of call-center agents.
Most techniques of likability estimation collect many annotations per sample since the annotations often include the variability of annotator evaluations.
Due to the inability to collect sufficient annotations, which are labeled by experts such as supervisor of call-center, from actual call-centers, the few annotations per call available cannot eliminate the variability.
We proposes two likability model training techniques from the few annotations per call based on annotators’ skill.
First, our technique provides reasonable labels, which eliminated from the influence of annotators’ skills, for model training from observed labels.
We also proposes a new neural network architecture that has a layer considering the variability of observed labels from each annotator.
Our proposal achieved 12.0% error reduction compared with baseline techniques.
Keyword (in Japanese) (See Japanese page) 
(in English) Likability / Call-center agent / Annotator / Neural Network / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 497, SP2018-94, pp. 197-202, March 2019.
Paper # SP2018-94 
Date of Issue 2019-03-07 (EA, SIP, SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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 EA2018-132 SIP2018-138 SP2018-94

Conference Information
Committee EA SIP SP  
Conference Date 2019-03-14 - 2019-03-15 
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 
Paper Information
Registration To SP 
Conference Code 2019-03-EA-SIP-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Likability Estimation Model Training of Call-center Agents Based on Annotators' Skills 
Sub Title (in English)  
Keyword(1) Likability  
Keyword(2) Call-center agent  
Keyword(3) Annotator  
Keyword(4) Neural Network  
1st Author's Name Hosana Kamiyama  
1st Author's Affiliation NTT Corporation (NTT)
2nd Author's Name Atsushi Ando  
2nd Author's Affiliation NTT Corporation (NTT)
3rd Author's Name Ryo Masumura  
3rd Author's Affiliation NTT Corporation (NTT)
4th Author's Name Satoshi Kobashikawa  
4th Author's Affiliation NTT Corporation (NTT)
5th Author's Name Yushi Aono  
5th Author's Affiliation NTT Corporation (NTT)
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Speaker Author-1 
Date Time 2019-03-15 10:50:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # EA2018-132, SIP2018-138, SP2018-94 
Volume (vol) vol.118 
Number (no) no.495(EA), no.496(SIP), no.497(SP) 
Page pp.197-202 
Date of Issue 2019-03-07 (EA, SIP, SP) 

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