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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
SELECTING N-LOWEST SCORES FOR TRAINING MOS PREDICTION MODELS Yuto Kondo, Hirokazu Kameoka, Kou Tanaka, Takuhiro Kaneko (NTT)  EA2023-94 SIP2023-141 SP2023-76 |
Automatic speech quality assessment (SQA) is a task to evaluate the quality of speech samples without resorting to time-... [more] | EA2023-94 SIP2023-141 SP2023-76 pp.196-201 |
| ET | 2023-03-15 11:35 |
Tokushima | Tokushima University (Primary: On-site, Secondary: Online) |
Development of a Teaching Strategy Switchable Viewing Support System with DTW Distance Ryota Tanaka, Naka Gotoda (Kagawa Univ), Mio Suzuki, Hirotake Kanisawa (SIT), Yuka Takai (OSU), Ryo Kanda, Yusuke Kometani, Rihito Yaegashi, Toshihiro Hayashi (Kagawa Univ) ET2022-85 |
In the practice of plastering, it is necessary to support achievement based on the setting of learning goals for skills ... [more] | ET2022-85 pp.161-167 |
| LOIS, ICM | 2022-01-27 14:50 |
Online | Online | Studies of task selection method for learning professional knowledge for newly appointed personnel. Teruyuki Sato, Akira Karasudani, Ichiro Watanabe, Shinji Kanda (Fujitsu Ltd) ICM2021-37 LOIS2021-35 |
In training new professional clerical work, assigning routine tasks or cases requiring advanced expertise, work experien... [more] | ICM2021-37 LOIS2021-35 pp.25-30 |
| R | 2017-10-20 15:30 |
Kumamoto | A Fundamental Study of Training Data Selection Method for Wind Turbine Health Management Using SCADA Data Akihisa Yasuda (UT), Jun Ogata (AIST), Yoko Furusawa (UT), Masahiro Murakawa (AIST), Hiroyuki Morikawa, Makoto Iida (UT) R2017-47 |
Wind turbines need to be stopped for a long period if the internal equipment breaks down. Therefore, it is important for... [more] | R2017-47 pp.17-22 |
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| PRMU, BioX | 2017-03-20 10:00 |
Aichi | Selection of Near-Boundary Data for Semi-Supervised Learning Ryohei Tanaka, Xiao Ding, Soichiro Ono, Akio Furuhata (Toshiba) BioX2016-33 PRMU2016-196 |
Semi-supervised learning (SSL) is a technique which makes use of unlabeled data in addition to labeled data to obtain be... [more] | BioX2016-33 PRMU2016-196 pp.1-6 |
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| PRMU, IBISML, IPSJ-CVIM [detail] | 2015-09-15 15:00 |
Ehime | Proposal of selection of training data using misdetected goodware for preventing misdetection of a static detector of malware Yasushi Okano, Atsutoshi Kumagai, Masaki Tanikawa, Yoshihito Oshima (NTT), Kenji Aiko, Kazumi Umehashi, Junichi Murakami (FFRI) PRMU2015-90 IBISML2015-50 |
A lot of variant and new malware is produced day by day, it is therefore the urgent need to countermeasure such as "unkn... [more] | PRMU2015-90 IBISML2015-50 pp.163-170 |
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| SP | 2015-08-21 16:15 |
Iwate | Iwate Prefectural Univ. | Training Data Selection for Acoustic Modeling Based on Submodular Optimization of Joint KL Divergence Taichi Asami, Ryo Masumura, Hirokazu Masataki, Manabu Okamoto, Sumitaka Sakauchi (NTT) SP2015-58 |
This paper provides a novel training data selection method to construct acoustic models for automatic speech recogniti... [more] |
SP2015-58 pp.45-50 |
| PRMU | 2014-12-12 13:00 |
Fukuoka | A proposal for data selection in self-training based cross dataset action recognition Takafumi Suzuki, Yu Wang, Jien Kato, Kenji Mase (Nagoya Univ) PRMU2014-80 |
In action recognition, in order to obtain high performance classifiers, it is necessary to feed the training algorithm e... [more] | PRMU2014-80 pp.85-89 |
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