Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SP, IPSJ-MUS, IPSJ-SLP [detail] |
2023-06-23 13:50 |
Tokyo |
(Primary: On-site, Secondary: Online) |
[Poster Presentation]
Parody Detection Based on Alignment Collapse Between Lyrics and Singing Voice Tomoki Ariga, Yosuke Higuchi (Waseda Univ.), Mitsunori Kanno, Rie Shigyo, Takato Mizuguchi, Naoki Okamoto (DAIICHIKOSHO), Tetsuji Ogawa (Waseda Univ.) SP2023-10 |
We propose a parody detection system for karaoke singing by evaluating alignment collapse between lyrics and singing voi... [more] |
SP2023-10 pp.48-53 |
AI |
2022-07-04 16:00 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Unsupervised Learning of a Dynamic Task Ordering Model for Crowdsourcing Ryo Yanagisawa (Waseda Univ.), Susumu Saito, Teppei Nakano (ifLab Inc.), Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.) AI2022-14 |
An unsupervised learning method for a dynamic task ordering model that optimizes the number of orders according to the d... [more] |
AI2022-14 pp.72-76 |
SP, IPSJ-MUS, IPSJ-SLP [detail] |
2022-06-18 15:00 |
Online |
Online |
[Poster Presentation]
Worker Filtering Criteria for Subjective Evaluation of Synthesized Voice Sound Quality Using Crowdsourcing Moe Yaegashi (Waseda Univ.), Susumu Saito, Teppei Nakano (Waseda Univ./ifLab.), Tetsuji Ogawa (Waseda Univ.) SP2022-24 |
We investigate the effect of filtering criteria of crowdworkers on the subjective evaluation results of synthesized voi... [more] |
SP2022-24 pp.104-109 |
SP, IPSJ-MUS, IPSJ-SLP [detail] |
2022-06-18 15:00 |
Online |
Online |
Unsupervised Training of Sequential Neural Beamformer Using Blindly-separated and Non-separated Signals Kohei Saijo, Tetsuji Ogawa (Waseda Univ.) SP2022-25 |
We present an unsupervised training method of the sequential neural beamformer (Seq-NBF) using the separated signals fro... [more] |
SP2022-25 pp.110-115 |
NLC, IPSJ-NL, SP, IPSJ-SLP [detail] |
2020-12-02 09:40 |
Online |
Online |
Fast End-to-End Speech Recognition with CTC and Mask Predict Yosuke Higuchi (Waseda Univ.), Hirofumi Inaguma (Kyoto Univ.), Shinji Watanabe (JHU), Tetsuji Ogawa, Tetsunori Kobayashi (Waseda Univ.) NLC2020-13 SP2020-16 |
We present a fast non-autoregressive (NAR) end-to-end automatic speech recognition (E2E-ASR) framework, which generates ... [more] |
NLC2020-13 SP2020-16 pp.1-6 |
NLC, IPSJ-NL, SP, IPSJ-SLP (Joint) [detail] |
2019-12-06 09:35 |
Tokyo |
NHK Science & Technology Research Labs. |
Time-domain convolutional denoising autoencoder for multi-channel speech enhancement Naohiro Tawara, Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.) SP2019-34 |
[more] |
SP2019-34 pp.1-6 |
PRMU, IPSJ-CVIM |
2019-05-30 10:50 |
Tokyo |
|
Calving sign detection system with cattle physical feature extraction from video frames Ryosuke Hyodo, Kazuma Sugawara (Waseda Univ.), Teppei Nakano, Makoto Akabane (Waseda Univ./iflab, inc.), Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.) PRMU2019-1 |
A calving sign detection system using cows' state-based and motion-based features is successfully designed. The develop... [more] |
PRMU2019-1 pp.1-6 |
PRMU, IPSJ-CVIM |
2019-05-30 11:05 |
Tokyo |
|
Suppression of False Alarms of Video Beef Cattle Calving Detection System Using Crowdsourcing for Rapid Deployment Yusuke Okimoto, Susumu Saito (Waseda Univ.), Teppei nakano, Makoto Akabane (Waseda Univ./iflab, inc.), Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.) PRMU2019-2 |
For rapid deployment of the beef cattle calving detection system by video, it is verified whether the system with crowds... [more] |
PRMU2019-2 pp.7-12 |
EA, SIP, SP |
2019-03-14 13:30 |
Nagasaki |
i+Land nagasaki (Nagasaki-shi) |
[Poster Presentation]
Diffuse noise reduction using adversarial denoising autoencoder Hikari Tanabe, Naohiro Tawara, Tetsunori Kobayashi (Waseda Univ.), Masaru Fujieda, Katagiri Kazuhiro, Takashi Yazu (OKI), Tetsuji Ogawa (Waseda Univ.) EA2018-125 SIP2018-131 SP2018-87 |
In this study, we attempted to remove diffuse noise by a model combining a prefilter and an adversarial denoising autoen... [more] |
EA2018-125 SIP2018-131 SP2018-87 pp.155-160 |
PRMU |
2018-12-14 10:45 |
Miyagi |
|
[Short Paper]
Calving prediction using behavioral information from video Kazuma Sugawara (Waseda Univ.), Teppei Nakano, Makoto Akabane (Waseda Univ./IFLab), Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.) PRMU2018-85 |
This study presents calving prediction methods focusing on cows' pre-calving behaviors and their changes.
Livestock far... [more] |
PRMU2018-85 pp.57-60 |
PRMU |
2018-12-14 14:40 |
Miyagi |
|
Calving sign detection with cattle state-based feature extraction from video frames Ryosuke Hyodo, Saki Yasuda (Waseda Univ.), Susumu Saito (Waseda Univ./iflab, inc.), Yusuke Okimoto (Waseda Univ.), Teppei Nakano, Makoto Akabane (Waseda Univ./iflab, inc.), Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.) PRMU2018-90 |
Requirements that camera-based automatic calving sign detection should meet are established and a system satisfying thes... [more] |
PRMU2018-90 pp.79-84 |
IBISML |
2018-03-05 17:00 |
Fukuoka |
Nishijin Plaza, Kyushu University |
Transformed Multiple Matrix Factorization: Towards Utilizing Heterogeneous Auxiliary Information Taira Tsuchiya (Waseda Univ.), Tomoharu Iwata (NTT), Tetsuji Ogawa (Waseda Univ.) IBISML2017-96 |
Matrix factorization is widely used for a variety of fields, such as computer vision, document analysis, signal processi... [more] |
IBISML2017-96 pp.41-48 |
SP, SIP, EA |
2017-03-02 09:00 |
Okinawa |
Okinawa Industry Support Center |
[Poster Presentation]
Use of the end of sentence and speaker-derived information in recurrent neural network language models for multiparty conversations. Hiroto Ashikawa, Naohiro Tawara (Waseda Univ.), Atsunori Ogawa, Tomoharu Iwata (NTT), Tetsuji Ogawa, Tetsunori Kobayashi (Waseda Univ.) EA2016-133 SIP2016-188 SP2016-128 |
Information on the end of sentence (EOS) and speaker alternation was exploited in recurrent neural network-based languag... [more] |
EA2016-133 SIP2016-188 SP2016-128 pp.287-290 |
SP |
2013-03-01 16:00 |
Aichi |
Daido University |
Current situations and issues of speaker recognition technologies Kanae Amino (NRIPS), Shunichi Ishihara (The Australian National University), Tetsuji Ogawa (Waseda Univ.), Takashi Osanai (NRIPS), Shingo Kuroiwa (Chiba Univ.), Takafumi Koshinaka (NEC), Koichi Shinoda (Tokyo Inst. of Tech.), Satoru Tsuge (Daido Univ.), Masafumi Nishida (Doshisha Univ.), Tomoko Matsui (ISM), Longbiao Wang (Nagaoka University of Technology) SP2012-131 |
Speaker recognition for recognizing who is speaking from his/her voice has been studied for 30 years. As the importance ... [more] |
SP2012-131 pp.63-70 |
IBISML |
2012-03-12 11:25 |
Tokyo |
The Institute of Statistical Mathematics |
Fully Bayesian speaker clustering based on hierarchical structured Dirichlet process mixture model Naohiro Tawara, Tetsuji Ogawa (Waseda Univ.), Shinji Watanabe (NTT/MERL), Atsushi Nakamura (NTT), Tetsunori Kobayashi (Waseda Univ.) IBISML2011-90 |
We proposed a novel speaker clustering method by estimating the structure of a fully Bayesian utterance generative model... [more] |
IBISML2011-90 pp.21-28 |
SP, NLC |
2008-12-09 10:25 |
Tokyo |
Waseda Univ. |
Hands-free speech recognition system for robot Kosuke Hosoya, Tetsuji Ogawa, Shinya Fujie, Daichi Watanabe, Yuhi Ichikawa, Hikaru Taniyama, Tetsunori Kobayashi (Waseda Univ.) NLC2008-25 SP2008-80 |
[more] |
NLC2008-25 SP2008-80 pp.7-12 |
SP |
2008-07-17 - 2008-07-19 |
Iwate |
Iwate Prefectural Univ. |
Dimensionality Reduction in Rescoring Using Likelihood Patterns Given by HMMs Tetsuji Ogawa, Tetsunori Kobayashi (Waseda Univ.) SP2008-55 |
We investigate dimensionality reduction of feature vectors in rescoring using likelihood patterns given by HMMs with lon... [more] |
SP2008-55 pp.73-78 |
SP |
2007-06-29 13:30 |
Fukushima |
The University of Aizu |
Hierarchical Spoken Word Recognition System Using Probabilistic Distances from a Group of Templates with Long-Time Structures Ken-ichi Kato, Tetsuji Ogawa, Tetsunori Kobayashi (Waseda Univ.) SP2007-21 |
[more] |
SP2007-21 pp.79-84 |