Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NLC |
2020-02-17 10:20 |
Tokyo |
Seikei University |
Analysing emergency care team leaders' eye gaze for understanding non-verbal behaviours in emergency care interaction Keiko Tsuchiya, Akira Taneichi (YCU), Kyota Nakamura (YCU Medical Cetnre), Takuma Sakai (YKH), Takeru Abe (YCU Medical Cetnre), Takeshi Saitoh (Kyutech) NLC2019-42 |
In emergency care interaction, a team leader collaborates with his members to safely perform medical procedures. This pr... [more] |
NLC2019-42 pp.33-36 |
NLP, NC (Joint) |
2020-01-25 09:30 |
Okinawa |
Miyakojima Marine Terminal |
On univariate continuous multimodal analysis and discrete multimodal analysis (2) Hideo Kanemitsu, Konno Hideaki (Hokkaido Univ. of Edu.) NLP2019-101 |
The (continuous) multimodal function of continuous variables defined by the authors focuses on the minimum (local) value... [more] |
NLP2019-101 pp.83-88 |
HCS |
2019-08-23 16:45 |
Osaka |
Jikei Institute |
Collection and Analysis of Human-System Multimodal Dialogue Data with Subjective Ratings Kazunori Komatani (Osaka Univ.), Shogo Okada (JAIST) HCS2019-33 |
Dialogue systems need to capture not only the verbal content that the user explicitly speaks but also the subtle behavio... [more] |
HCS2019-33 pp.21-26 |
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] |
2019-06-17 16:15 |
Okinawa |
Okinawa Institute of Science and Technology |
Imputation of Missing Time-Series Multimodal Data with Variational Autoencoder Ryoichi Kojima, Shinya Wada, Kiyohito Yoshihara (KDDI Research) IBISML2019-8 |
Data is often missing and that results in negative effects on subsequent data analysis and creating machine learning mod... [more] |
IBISML2019-8 pp.51-55 |
MVE, ITE-HI, ITE-SIP [detail] |
2019-06-10 10:30 |
Tokyo |
|
Impression Prediction of Oral Presentation Using LSTM with Dot-product Attention Mechanism Shengzhou Yi, Xueting Wang, Toshihiko Yamasaki (UTokyo) MVE2019-1 |
For automatically evaluating oral presentation, we propose an end-to-end system to predict audience’s impression on spee... [more] |
MVE2019-1 pp.1-6 |
SP |
2019-01-27 11:30 |
Ishikawa |
Kanazawa-Harmonie |
Multimodal Data Augmentation for Visual Speech Recognition using Deep Canonical Correlation Analysis Masaki Shimonishi, Satoshi Tamura, Satoru Hayamizu (Gifu University) SP2018-60 |
This paper proposes ta new data augmentation strategy for deep learning, in which feature vectors in one modality can be... [more] |
SP2018-60 pp.41-45 |
PRMU |
2018-12-14 14:10 |
Miyagi |
|
What Affects Visual Ad Clicks in Social Media Platforms? Yuki Iwazaki, Kota Yamaguchi (CyberAgent, Inc.) PRMU2018-88 |
In the online advertisement, high-quality prediction on click-through rate (CTR) is crucial for delivering the optimal a... [more] |
PRMU2018-88 pp.67-72 |
HCS |
2017-08-21 14:10 |
Tokyo |
Seikei University |
Meeting Extracts for Group Discussions using Multimodal Convolutional Neural Networks Fumio Nihei, Yukiko Nakano, Yutaka Takase (Seikei Univ.) HCS2017-57 |
With the goal of extracting meeting minutes from group discussion corpus, this study proposes multimodal fusion models b... [more] |
HCS2017-57 pp.55-59 |
PRMU, IE, MI, SIP |
2017-05-25 14:10 |
Aichi |
|
Dominant Line Extraction in Multimodal GIS Data Tomohiro Nishikawa, Yuichi Tanaka (TUAT) SIP2017-8 IE2017-8 PRMU2017-8 MI2017-8 |
In this report, we propose a multiple line extraction method from multimodal GIS data distributed in high dimensional sp... [more] |
SIP2017-8 IE2017-8 PRMU2017-8 MI2017-8 pp.43-48 |
SP, IPSJ-SLP, NLC, IPSJ-NL (Joint) [detail] |
2016-12-20 10:20 |
Tokyo |
NTT Musashino R&D |
Constructing a Japanese multimodal corpus from emotional monologues and dialogues Nurul Lubis (NAIST), Randy Gomez (HRI), Sakriani Sakti (NAIST), Keisuke Nakamura (HRI), Koichiro Yoshino, Satoshi Nakamura (NAIST), Kazuhiro Nakadai (HRI) SP2016-51 |
To fully incorporate emotion into human-computer interaction, rich sets of labeled emotional data is prerequisite. Howev... [more] |
SP2016-51 pp.9-10 |
WIT, HI-SIGACI |
2016-12-14 16:10 |
Tokyo |
AIST Tokyo Waterfront |
Training effects of automated social skills trainer for users of autism spectrum disorders Hiroki Tanaka (NAIST), Hideki Negoro (Nara University of Education), Hidemi Iwasaka (Heartland Shigisan), Satoshi Nakamura (NAIST) WIT2016-52 |
We have attempted to automate one or several parts of social skills training through multimodal human-computer interacti... [more] |
WIT2016-52 pp.39-44 |
IBISML |
2016-11-17 14:00 |
Kyoto |
Kyoto Univ. |
[Poster Presentation]
Analysis of Multimodal Deep Neural Networks
-- Towards the elucidation of the modality integration mechanism -- Yoh-ichi Mototake, Takashi Ikegami (unit of Tokyo) IBISML2016-97 |
With the rapid development of information technology in recent years,
several machine learning algorithms that integra... [more] |
IBISML2016-97 pp.369-373 |
PRMU, IPSJ-CVIM, MVE [detail] |
2015-01-22 15:00 |
Nara |
|
Automatic learning and recognition of unknown object by image search and keyword search Shunichiro Mizuno, Osamu Hasegawa (Tokyo Tech) PRMU2014-96 MVE2014-58 |
We should teach the feature to the computer system to recognize the real world object. This is very laborious work. In o... [more] |
PRMU2014-96 MVE2014-58 pp.105-110 |
PRMU |
2014-03-13 13:15 |
Tokyo |
|
[Special Talk]
Trial Realization of Associative Search for Media Understanding Miki Haseyama (Hokkaido Univ.) PRMU2013-180 |
This paper presents a new associative search system for enhancing serendipity which collaboratively use several unstruct... [more] |
PRMU2013-180 pp.73-77 |
SP |
2010-06-17 16:15 |
Fukuoka |
Kyushu University |
Decision Fusion using Boosting Method for Multi-Modal Voice Activity Detection Shin'ichi Takeuchi, Takashi Hashiba, Satoshi Tamura, Satoru Hayamizu (Gifu Univ.) SP2010-26 |
In this paper, we propose a multi-modal voice activity detection system
(VAD) that uses audio and visual information. ... [more] |
SP2010-26 pp.25-30 |
PRMU, SP, MVE, CQ |
2010-01-22 14:50 |
Kyoto |
Kyoto Univ. |
Multimodal speech recognition using multimodal voice activity detection Satoshi Tamura, Masato Ishikawa, Takashi Hashiba, Shin'ichi Takeuchi, Satoru Hayamizu (Gifu Univ.) CQ2009-105 PRMU2009-204 SP2009-145 MVE2009-127 |
Audio-Visual Automatic Speech Recognition (AVASR) has been developed to enhance the robustness in noisy environments, us... [more] |
CQ2009-105 PRMU2009-204 SP2009-145 MVE2009-127 pp.345-350 |
SP, NLC |
2008-12-10 16:10 |
Tokyo |
Waseda Univ. |
Driver's irritation detection using speech recognition results Lucas Malta, Chiyomi Miyajima, Akira Ozaki, Norihide Kitaoka, Kazuya Takeda (Nagoya Univ.) NLC2008-65 SP2008-120 |
In this work we present our efforts towards the multi-modal estimation of a driver's affective state under naturalistic ... [more] |
NLC2008-65 SP2008-120 pp.245-248 |
CQ |
2007-07-13 14:00 |
Hokkaido |
Shiretoko Prince Hotel Kazenamiki |
Implementation and basic evaluation of handover management scheme supporting multiple connections in multimodal environment Kazuya Tsukamoto, Yuki Nakano, Takeshi Yamaguchi (KIT), Shigeru Kashihara (NAIST), Yuji Oie (KIT) CQ2007-33 |
With the wide spread of various data link technologies, in the near future, mobile nodes (MNs) will automatically select... [more] |
CQ2007-33 pp.113-118 |
SP |
2007-05-31 11:30 |
Kyoto |
ATR |
A study on multimodal speech recognition for spoken dialogue systems Shunsuke Takayama, Toshihide Matsuo, Koji Iwano, Sadaoki Furui (Tokyo Tech) SP2007-4 |
This paper describes speaker-independent multimodal speech recognition toward constructing multimodal spoken dialogue sy... [more] |
SP2007-4 pp.19-24 |
NC |
2006-01-24 11:15 |
Hokkaido |
Hokkaido Univ. |
Embedding of labeled multimodal data Yuki Shinada, Masashi Sugiyama (Tokyo Tech.) |
In order to improve the recognition accuracy of high dimensional patterns, it is important to appropriately reduce the n... [more] |
NC2005-102 pp.25-30 |