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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| HCS, CNR | 2023-11-05 14:40 |
Tokyo | Kogakuin University (Primary: On-site, Secondary: Online) |
Development of a human-friendly robot using a behavioral model based on emotion recognition Chika Kanesaki, Kenji Matsuzaka (NIT, UC)  CNR2023-14 HCS2023-76 |
In smooth communication between humans, the recognition and understanding of nonverbal information caused by emotions is... [more] | CNR2023-14 HCS2023-76 pp.38-44 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2023-06-23 13:50 |
Tokyo | (Primary: On-site, Secondary: Online) |
Speech Emotion Recognition based on Emotional Label Sequence Estimation Considering Phoneme Class Attribute Ryotaro Nagase, Takahiro Fukumori, Yoichi Yamashita (Ritsumeikan Univ.) SP2023-9 |
Recently, many researchers have tackled speech emotion recognition (SER), which predicts emotion conveyed by speech. In ... [more] | SP2023-9 pp.42-47 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2023-06-23 13:50 |
Tokyo | (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Generation of colored subtitle images based on emotional information of speech utterances Fumiya Nakamura (Kobe Univ.), Ryo Aihara (Mitsubishi Electric), Ryoichi Takashima, Tetsuya Takiguchi (Kobe Univ.), Yusuke Itani (Mitsubishi Electric) SP2023-11 |
Conventional automatic subtitle generation systems based on speech recognition do not take into account paralinguistic i... [more] | SP2023-11 pp.54-59 |
| NC, MBE (Joint) |
2023-03-15 13:50 |
Tokyo | The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
Comparison of classification accuracy by frequency band restriction on emotion recognition from EEG Raiki Yamane, Shin'ichiro Kanoh (SIT) NC2022-115 |
Accuracy of emotion classification in deep learning when frequency band restriction is used as a preprocessing method fo... [more] | NC2022-115 pp.127-132 |
| IPSJ-SLDM, RECONF, VLD [detail] | 2023-01-24 10:55 |
Kanagawa | Raiosha, Hiyoshi Campus, Keio University (Primary: On-site, Secondary: Online) |
Study on Wireless Transmission Data Reduction Method and Its Implementation in Emotion Recognition System Using Electroencephalogram Yuuki Harada, Daisuke Kanemoto, Tetsuya Hirose (Osaka Univ.) VLD2022-66 RECONF2022-89 |
Recently, there has been a great deal of research on emotion recognition and its application using electroencephalogram.... [more] | VLD2022-66 RECONF2022-89 pp.40-44 |
| HCGSYMPO (2nd) |
2021-12-15 - 2021-12-17 |
Online | Online | Emotion discrimination model for learning spatio-temporal frequency information of EEG using SNN Rio Kanda, Chika Sugimoto (Yokohama National Univ.) |
In order to achieve high accuracy in emotion recognition based on EEG, it is considered effective to simultaneously lear... [more] | |
| HCGSYMPO (2nd) |
2021-12-15 - 2021-12-17 |
Online | Online | Modality-Independent Emotion Recognition Based on Hyper-Hemispherical Embedding and Latent Representation Unification Using Multimodal Deep Neural Networks Seiichi Harata, Takuto Sakuma, Shohei Kato (NIT) |
This study aims to obtain a mathematical representation of emotions (an emotion space) common to modalities. The propos... [more] |
|
| AI | 2020-12-11 10:55 |
Shizuoka | Online and HAMAMATSU ACT CITY (Primary: On-site, Secondary: Online) |
An application of Differentiable Neural Architecture Search to Multimodal Neural Networks Yushiro Funoki, Satoshi Ono (Kagoshima Univ) AI2020-11 |
This paper proposes a method that designs an architecture of a deep neural network for multimodal sequential data using ... [more] | AI2020-11 pp.52-56 |
| HPB (2nd) |
2020-02-14 16:10 |
Kanagawa | Performance evaluation of bullying voice judgement system using emotion analysis based on SVM Takahiro Ueno, Shintaro Mori, Masayoshi Ohashi (Fukuoka Univ.) |
Bullying is a serious problem all over the world, and bullying detection is significant to protect victims. In this pape... [more] | ||
| HCGSYMPO (2nd) |
2019-12-11 - 2019-12-13 |
Hiroshima | Hiroshima-ken Joho Plaza (Hiroshima) | Crosslingual Emotion Recognition using English and Japanese Speech Data Yuta Nirasawa, Atom Scotto, Ryota Sakuma, Yuki Hujita, Keiich Zempo (Tsukuba Univ.) |
Since reasearch in Speech Emotion Recognition(SER) is performed with mostly English data, applying these models to Japan... [more] | |
| NLC, IPSJ-NL, SP, IPSJ-SLP (Joint) [detail] |
2019-12-06 16:25 |
Tokyo | NHK Science & Technology Research Labs. | An evaluation of representation learning using phoneme posteriorgrams and data augmentation in speech emotion recognition Shintaro Okada (Nagoya Univ.), Atsushi Ando (Nagoya Univ./NTT), Tomoki Toda (Nagoya Univ.) SP2019-43 |
This paper presents a new speech emotion recognition method based on representation learning and data augmentation. To ... [more] |
SP2019-43 pp.91-96 |
| TL | 2019-03-18 16:20 |
Tokyo | Waseda University | Examination of Emotion Estimation Technique of Driver Using Biomedical Signal Yusuke Shoji, Atsushi Ito, Hiroyuki Hatano (Utsunomiya Univ.) TL2018-64 |
In recent years, various driving support systems such as automatic braking and vehicle detection for preventing rear-end... [more] | TL2018-64 pp.77-81 |
| AI | 2018-12-07 15:55 |
Fukuoka | Toyoaki Kuwahara, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) AI2018-30 |
The emotion estimation by speech makes it possible to estimate with higher precision with the development of deep learni... [more] | AI2018-30 pp.25-29 |
|
| RCC, MICT | 2018-05-25 14:20 |
Tokyo | Tokyo Big Sight | Learning and recognition with neural network of heart beats sensed by WBAN for stress estimate for rehabilitation Yukihiro Kinjo, Yoshitomo Sakuma, Ryuji Kohno (YNU) RCC2018-21 MICT2018-21 |
In rehabilitation, approach according to personality is important. So we estimate patients' emotion by neural network(N... [more] |
RCC2018-21 MICT2018-21 pp.101-104 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:00 |
Okinawa | [Poster Presentation]
Acoustic analysis of speech for emergency speech detection of voicemail Matsuto Hori (Meiji Univ.), Hosana Kamiyama, Satoshi Kobashikawa (NTT), Shigeki Sagayama (Meiji Univ.) EA2017-112 SIP2017-121 SP2017-95 |
In this paper, we investigate the effectiveness of acoustic features for detecting urgency in voicemail. In previous res... [more] | EA2017-112 SIP2017-121 SP2017-95 pp.63-68 |
|
| HCS | 2018-01-26 10:50 |
Kagoshima | Daiichi Institute of Technology | The effects of cultural view of the self on recognition of emotions through eyes or mouth Shinnosuke Ikeda (Univ. of Tokyo) HCS2017-67 |
Facial expressions provide primary cues for emotions. We are capable of making some facial expressions deliberately, eve... [more] | HCS2017-67 pp.7-12 |
| SP | 2017-08-30 11:00 |
Kyoto | Kyoto Univ. | [Poster Presentation]
Emotion Recognition in Speech Using Deep Neural Network Li ShiChuan, Tomoki Ishikawa, Masahiro Niitsuma, Keisuke Imoto, Yoichi Yamashita (Ritsumeikan Univ.) SP2017-24 |
Speech conveys not only linguistic information but also paralinguistic and non-linguistic information such as emotions，a... [more] | SP2017-24 pp.25-28 |
| PRMU | 2016-12-15 15:30 |
Tottori | [Invited Talk]
What we see/do not see ?
-- The 2nd Grand Challenge of PRMU -- Atsushi Nakazawa (Kyot Univ.) PRMU2016-115 |
The first grand challenge showed the list of problems in PRMU in 2008. In the meantime, a lot of state of the art ... [more] | PRMU2016-115 p.15 |
|
| EA, SP, SIP | 2016-03-29 15:40 |
Oita | Beppu International Convention Center B-ConPlaza | Study of Feature in Emotion Recognition Using EEG during Music Listening Hiroki Itoga, Yoshikazu Washizawa (UEC) EA2015-135 SIP2015-184 SP2015-163 |
Human mind has been interested and researched. Human emotion is a kind of functions of mind. Emotion estimation may gui... [more] |
EA2015-135 SIP2015-184 SP2015-163 pp.385-390 |
| HCGSYMPO (2nd) |
2015-12-16 - 2015-12-18 |
Toyama | Toyama International Conference Center | Effect Evaluation of Discriminative Models and Data Input Conditions on Emotion Recognition from EEG Miku Yanagimoto, Chika Sugimoto (YNU) |
Machine learning methods for human emotion recognition using biosignals are proposed, but high accuracy has not been ach... [more] | |
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