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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIS | 2024-03-14 13:00 |
Kanagawa | Kanagawa Institute of Technology (Primary: On-site, Secondary: Online) |
On Time-Position Detection of Signals under Noise Considering Threshold
-- Applications of Fractal Dimension Filters -- Hideo Shibayama (Shibaura Institute of Technology), Yoshiaki Makabe (Kanagawa Institute of Technology), Kenji Muto (Shibaura Institute of Technology), Tomoaki Kimura (Kanagawa Institute of Technology)  SIS2023-45 |
Conflicts due to neighborhood noise can occur even when the sound pressure level is low. In such cases, the sound pressu... [more] | SIS2023-45 pp.1-6 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Improving training recipe of Remixed2Remixed for speech enhancement Li Li, Shogo Seki (CyberAgent) EA2023-95 SIP2023-142 SP2023-77 |
In the use of deep learning for speech enhancement, supervised learning models that use pairs of clean speech and artifi... [more] | EA2023-95 SIP2023-142 SP2023-77 pp.202-207 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 16:35 |
Okinawa | (Primary: On-site, Secondary: Online) |
Evaluations of Multi-channel Blind Source Separation for Speech Recognition in Car Environments Yutsuki Takeuchi, Natsuki Ueno, Nobutaka Ono (Tokyo Metropolitan Univ.), Takashi Takazawa, Shuhei Shimanoe, Tomoki Tanemura (MIRISE Technologies) EA2023-127 SIP2023-174 SP2023-109 |
In car environments, speech recognition is difficult due to various types of noise. For this issue, speech enhancement b... [more] | EA2023-127 SIP2023-174 SP2023-109 pp.388-393 |
| SIS | 2023-12-08 09:50 |
Aichi | Sakurayama Campus, Nagoya City University (Primary: On-site, Secondary: Online) |
Time-position Detection of Signal under Background Noise Using Fractal Dimensional Filter Hideo Shibayama (Shibaura Institute of Technology), Yoshiaki Makabe (Kanagawa Institute of Technology), Kenji Muto (Shibaura Institute of Technology), Tomoaki Kimura (Kanagawa Institute of Technology) SIS2023-34 |
Conflicts due to neighborhood noise occur even when noise levels are lower than those specified by environmental standar... [more] | SIS2023-34 pp.55-60 |
| SP, NLC, IPSJ-SLP, IPSJ-NL [detail] | 2023-12-03 09:30 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
Enhancing Recognition of Rare Words in ASR through Error Detection and Context-Aware Error Correction Jiajun He, Zekun Yang, Tomoki Toda (Nagoya Univ.) NLC2023-16 SP2023-36 |
Automatic speech recognition (ASR) systems often suffer from errors, particularly when recognizing rare words. These err... [more] | NLC2023-16 SP2023-36 pp.13-18 |
| WIT, SP, IPSJ-SLP [detail] | 2023-10-14 16:40 |
Fukuoka | Kyushu Institute of Technology (Primary: On-site, Secondary: Online) |
Sequence-to-sequence Voice Conversion for Electrolaryngeal Speech Enhancement with Multi-stage Pretraining and Fine-tuning Techniques Ding Ma, Lester Phillip Violeta, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) SP2023-32 WIT2023-23 |
Sequence-to-sequence (seq2seq) voice conversion (VC) models have great potential for electrolaryngeal (EL) speech to nor... [more] | SP2023-32 WIT2023-23 pp.27-32 |
| WIT, SP, IPSJ-SLP [detail] | 2023-10-14 17:05 |
Fukuoka | Kyushu Institute of Technology (Primary: On-site, Secondary: Online) |
Electrolaryngeal Speech Enhancement through Strong Linguistic Encoding Methods Lester Phillip Violeta, Wen-Chin Huang, Ding Ma, Ryuichi Yamamoto, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) SP2023-33 WIT2023-24 |
Although pretraining and fine-tuning approaches have proven to work well in speech intelligibility enhancement, various ... [more] | SP2023-33 WIT2023-24 pp.33-38 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2023-06-23 13:50 |
Tokyo | (Primary: On-site, Secondary: Online) |
Streaming End-to-End speech recognition using a CTC decoder with substituted linguistic information Tatsunari Takagi (TUT), Atsunori Ogawa (NTT), Norihide Kitaoka, Yukoh Wakabayashi (TUT) SP2023-12 |
Speech recognition technology has been employed in various fields due to the enhancement of speech recognition model acc... [more] | SP2023-12 pp.60-64 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 15:10 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
[Invited Talk]
-- Yuma Koizumi (Google Research) PRMU2022-87 IBISML2022-94 |
Machine learning tasks that deal with acoustic signals can be broadly classified into "recognizing sounds" and "generati... [more] | PRMU2022-87 IBISML2022-94 p.149 |
| SIS | 2023-03-03 11:10 |
Chiba | Chiba Institute of Technology (Primary: On-site, Secondary: Online) |
Investigation of introducing data augmentation methods to improve speech enhancement performance Reito Kasuga, Yosuke Sugiura, Nozomiko Yasui, Tetsuya Shimamura (Saitama Univ.) SIS2022-52 |
The field of speech enhancement has been extensively researched worldwide, and many speech enhancement methods have been... [more] | SIS2022-52 pp.64-69 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 11:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
Analysis of Noisy-target Training for DNN-based speech enhancement and investigation towards its practical use Takuya Fujimura, Tomoki Toda (Nagoya Univ.) EA2022-112 SIP2022-156 SP2022-76 |
Deep neural network (DNN)-based speech enhancement usually uses a clean speech as a training target. However, it is hard... [more] | EA2022-112 SIP2022-156 SP2022-76 pp.221-226 |
| SIS, ITE-BCT | 2022-10-13 14:15 |
Aomori | Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Toward Improving Speech Naturalness Introducing a Capsule Structure for Speech Enhancement Networks Reito Kasuga, Tetsuya Shimamura, Yosuke Sugiura, Nozomiko Yasui (Saitama Univ.) SIS2022-12 |
Although the field of speech enhancement has been extensively studied around the world, phase tends to be neglected comp... [more] | SIS2022-12 pp.7-12 |
| SIP | 2022-08-26 14:08 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Study on Bone-conducted Speech Enhancement Using Vector-quantized Variational Autoencoder and Gammachirp Filterbank Cepstral Coefficients Quoc-Huy Nguyen, Masashi Unoki (JAIST) SIP2022-71 |
Bone-conducted (BC) speech potentially avoids the undesired effects on recorded speech due to background noise or reverb... [more] | SIP2022-71 pp.109-114 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-01 13:10 |
Okinawa | (Primary: On-site, Secondary: Online) |
The upper limit of subjective intelligibility score of speech enhancement using IRM
-- comparison between laboratory and crowdsourcing experiments -- Ayako Yamamoto, Toshio Irino (Wakayama Univ.), Shoko Araki, Kenichi Arai, Atsunori Ogawa, Keisuke Kinoshita, Tomohiro Nakatani (NTT) EA2021-74 SIP2021-101 SP2021-59 |
We performed subjective speech intelligibility experiments in a laboratory and using crowdsourcing to get a fundamental ... [more] | EA2021-74 SIP2021-101 SP2021-59 pp.64-69 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-18 15:00 |
Online | Online | Speech Intelligibility Experiments using crowdsourcing
-- from designing Web page to Data screening -- Ayako Yamamoto, Toshio Irino (Wakayama Univ.), Kenichi Arai, Shoko Araki, Atsunori Ogawa, Keisuke Kinoshita, Tomohiro Nakatani (NTT) SP2021-5 |
Many subjective experiments have been performed to develop objective speech intelligibility measures, but the novel coro... [more] | SP2021-5 pp.25-30 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-19 09:30 |
Online | Online | [Invited Talk]
Toward a Unification of Various Speech Processing Tasks Based on End-to-End Neural networks Shinji Watanabe (CMU) SP2021-8 |
This presentation will introduce the recent progress of speech processing technologies based on end-to-end neural networ... [more] | SP2021-8 p.38 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-03 14:05 |
Online | Online | [Poster Presentation]
Comparison of speech intelligibility results between laboratory and crowd-sourcing experiments Ayako Yamamoto, Toshio Irino (Wakayama Univ.), Kenichi Arai, Shoko Araki, Atunori Ogawa, Keisuke Kinoshita, Tomohiro Nakatani (NTT) EA2020-73 SIP2020-104 SP2020-38 |
Many subjective experiments have been performed to develop objective speech intelligibility measure. But COVID-19 has ma... [more] | EA2020-73 SIP2020-104 SP2020-38 pp.79-84 |
| SIS | 2020-12-01 11:25 |
Online | Online | [Tutorial Lecture]
A Theory for Controlling Musical Noise Based on Higher-Order Statistics Ryoichi Miyazaki, Takuya Fujimura (NITTC) SIS2020-30 |
Although nonlinear speech enhancement methods can significantly eliminate background noise, it is known to generate musi... [more] | SIS2020-30 pp.18-23 |
| SIS | 2020-03-06 15:00 |
Saitama | Saitama Hall (Cancelled but technical report was issued) |
Adversarial Training using Self-Attention Architecture for Speech Enhancement Network Yosuke Sugiura, Shimamura Tetsuya (Saitama Univ.) SIS2019-59 |
In this paper, we propose a new adversarial training for improving performance of the speech enhancement network. In th... [more] |
SIS2019-59 pp.125-129 |
| SP, EA, SIP | 2020-03-02 15:45 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Performance evaluation of distilling knowledge using encoder-decoder for CTC-based automatic speech recognition systems Takafumi Moriya, Hiroshi Sato, Tomohiro Tanaka, Takanori Ashihara, Ryo Masumura, Yusuke Shinohara (NTT) EA2019-131 SIP2019-133 SP2019-80 |
We present a novel training approach for connectionist temporal classification (CTC) -based automatic speech recognition... [more] | EA2019-131 SIP2019-133 SP2019-80 pp.175-180 |
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