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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-18 13:00 |
Online | Online | F0 estimation of speech based on l2-norm regularized TV-CAR analysis Keiichi Funaki (Univ. of the Ryukyus)  SP2021-2 |
Linear Prediction (LP) is the most successful speech analysis in speech processing, including speech coding implemented ... [more] |
SP2021-2 pp.7-12 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-19 13:00 |
Online | Online | Study on the background cancellation system for speech privacy Jiangning Huang, Akinori Ito (Tohoku Univ.) SP2021-14 |
Evacuation centers at the time of disaster do not have sufficient sound insulation to maintain sound privacy. In this st... [more] | SP2021-14 pp.57-62 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-03 13:05 |
Online | Online | [Invited Talk]
* Masahito Togami (LINE) EA2020-64 SIP2020-95 SP2020-29 |
Recently, deep learning based speech source separation has been evolved rapidly. A neural network (NN) is usually learne... [more] | EA2020-64 SIP2020-95 SP2020-29 pp.27-32 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-03 14:05 |
Online | Online | [Poster Presentation]
A unified source-filter network for neural vocoder Reo Yoneyama, Yi-Chiao Wu, Tomoki Toda (Nagoya Univ.) EA2020-69 SIP2020-100 SP2020-34 |
In this paper, we propose a method to develop a neural vocoder using a single network based on the source-filter theory.... [more] | EA2020-69 SIP2020-100 SP2020-34 pp.57-62 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-03 14:05 |
Online | Online | [Poster Presentation]
Noise-robust time-domain speech separation with basis signals for noise Kohei Ozamoto (Tokyo Tech), Koji Iwano (TCU), Kuniaki Uto, Koichi Shinoda (Tokyo Tech) EA2020-70 SIP2020-101 SP2020-35 |
Recently, speech separation using deep learning has been extensively studied. TasNet, a time-domain method that directly... [more] | EA2020-70 SIP2020-101 SP2020-35 pp.63-67 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-04 16:10 |
Online | Online | Estimation of imagined speech from electrocorticogram with an encoder-decoder model Kotaro Hayashi, Shuji Komeiji (TUAT), Takumi Mitsuhashi, Yasushi Iimura, Hiroharu Suzuki, Hidenori Sugano (Juntendo Univ.), Koichi Shinoda (TokyoTech), Toshihisa Tanaka (TUAT) EA2020-87 SIP2020-118 SP2020-52 |
Recent advances in signal processing and machine learning technologies have made it possible to estimate and reconstruct... [more] | EA2020-87 SIP2020-118 SP2020-52 pp.164-169 |
| EA | 2020-12-14 10:05 |
Online | Online | Speech Signal Detection Based on Bayesian Estimation by Observing Air-Conducted Speech under Existence of Surrounding Noise with Aid of Bone-Conducted Speech Akira Ikuta, Hisako Orimoto (Prefectural Univ. of Hiroshima), Kouji Hasegawa (Hiroshima Prefectural Technology Research Inst.) EA2020-48 |
When applying speech recognition systems to actual circumstances such as inspection and maintenance operations in indust... [more] | EA2020-48 pp.13-18 |
| HIP | 2020-10-09 16:45 |
Online | Online | Using Pupillary Responses to Measure Cognitive Load of Japanese Synthetic Speech mixed with Noise Mateusz Dubiel (UniStrath), Minoru Nakayama (Tokyo Tech.), Xin Wang (NII) HIP2020-51 |
Pupillometry has recently been introduced as a method to evaluate cognitive workload of synthetic speech. Prior research... [more] | HIP2020-51 pp.93-96 |
| SIS | 2020-03-06 14:40 |
Saitama | Saitama Hall (Cancelled but technical report was issued) |
An implusive noise detection method in noisy speech signals using the short time Fourier transform Sho Hasegawa, Eisuke Horita (Kanazawa Univ.) SIS2019-58 |
The short-time Fourier transform based method to detect impulsive noises from speech signals is expressed. Especially W... [more] | SIS2019-58 pp.119-124 |
| NC, MBE (Joint) |
2020-03-05 14:35 |
Tokyo | University of Electro Communications (Cancelled but technical report was issued) |
Detection of covert-speech-related potentials Sho Tsukiyama, Toshimasa Yamazaki (KIT) MBE2019-87 |
Recently, Brain-Computer Interfaces (BCIs) using speeches for communications have been researched by electroencephalogra... [more] | MBE2019-87 pp.35-40 |
| SP, EA, SIP | 2020-03-02 09:20 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Investigation of neural speech rate conversion with multi-speaker WaveNet vocoder Takuma Okamoto (NICT), Keisuke Matsubara (Kobe Univ./NICT), Tomoki Toda (Nagoya Univ./NICT), Yoshinori Shiga, Hisashi Kawai (NICT) EA2019-101 SIP2019-103 SP2019-50 |
Speech rate conversion technology, which can expand or compress speech waveforms without changing pitch of sound, is con... [more] | EA2019-101 SIP2019-103 SP2019-50 pp.1-6 |
| SP, EA, SIP | 2020-03-02 13:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Data augmentation for ASR system by using locally time-reversed speech
-- Temporal inversion of feature sequence -- Takanori Ashihara, Tomohiro Tanaka, Takafumi Moriya, Ryo Masumura, Yusuke Shinohara, Makio Kashino (NTT) EA2019-110 SIP2019-112 SP2019-59 |
Data augmentation is one of the techniques to mitigate overfitting and improve robustness against several acoustic varia... [more] | EA2019-110 SIP2019-112 SP2019-59 pp.53-58 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Semi-supervised Self-produced Speech Enhancement and Suppression Based on Joint Source Modeling of Air- and Body-conducted Signals Using Variational Autoencoder Shogo Seki, Moe Takada, Kazuya Takeda, Tomoki Toda (Nagoya Univ.) EA2019-140 SIP2019-142 SP2019-89 |
This paper proposes a semi-supervised method for enhancing and suppressing self-produced speech, using a variational aut... [more] | EA2019-140 SIP2019-142 SP2019-89 pp.225-230 |
| EMM | 2020-01-27 13:00 |
Miyagi | Tohoku Univ. | Suppression of Dialog System Speech by Embedding Marker Signal into High Frequency Band Shunsuke Saga, Akinori Ito (Tohoku Univ.) EMM2019-94 |
Spoken dialog systems have become popular and are used in a home environment, such as smart speakers. A problem will occ... [more] | EMM2019-94 pp.1-6 |
| EA | 2019-12-12 14:25 |
Fukuoka | Kyushu Inst. Tech. | Performance improvement of speech enhancement network by multitask learning including noise information Haruki Tanaka (NITTC), Yosuke Sugiura, Nozomiko Yasui, Tetsuya Shimamura (Saitama Univ.), Ryoichi Miyazaki (NITTC) EA2019-70 |
In the signal processing field, there is a growing interest in speech enhancement.Recently, a lot of speech enhancement ... [more] | EA2019-70 pp.31-36 |
| EA | 2019-12-13 11:20 |
Fukuoka | Kyushu Inst. Tech. | Listening difficulty rating prediction model using STOI-type objective intelligibility index for outdoor public address speech Keita Noguchi, Yosuke Kobayashi, Jay Kishigami (Muroran-IT), Kiyohiro Kurisu (TOA) EA2019-76 |
An outdoor public address (PA) system is indispensable for emergency broadcasting during the occurrence of disasters, an... [more] | EA2019-76 pp.71-78 |
| NLC, IPSJ-NL, SP, IPSJ-SLP (Joint) [detail] |
2019-12-06 13:55 |
Tokyo | NHK Science & Technology Research Labs. | [Poster Presentation]
Time-Varying Complex AR speech analysis based on l2-norm regularization Keiichi Funaki (Univ. of the Ryukyus) SP2019-41 |
Linear prediction (LP) is a mathematical operation estimating an all-pole spectrum from the speech signal. It is an ess... [more] |
SP2019-41 pp.73-77 |
| WIT, SP | 2019-10-27 09:00 |
Kagoshima | Daiichi Institute of Technology | Extraction of linguistic representation and syllable recognition from EEG signal of speech-imagery Kentaro Fukai, Hidefumi Ohmura, Kouichi Katsurada (Tokyo Univ. of Science), Satoka Hirata, Yurie Iribe (Aichi Prefectural Univ.), Mingchua Fu, Ryo Taguchi (Nagoya Inst. of Technology), Tsuneo Nitta (Waseda Univ./Toyohashi Univ. of Technology) SP2019-28 WIT2019-27 |
Speech imagery recognition from Electroencephalogram (EEG) is one of the challenging technologies for non-invasive brain... [more] | SP2019-28 WIT2019-27 pp.63-68 |
| WIT, SP | 2019-10-27 09:20 |
Kagoshima | Daiichi Institute of Technology | Word Recognition using word likelihood vector from speech-imagery EEG Satoka Hirata, Yurie Iribe (Aichi Prefectual Univ.), Kentaro Fukai, Kouichi Katsurada (Tokyo Univ. of Science), Tsuneo Nitta (Waseda Univ./Toyohashi Univ. of Tech.) SP2019-29 WIT2019-28 |
Previous research suggests that humans manipulate the machine using their electroencephalogram called BCI （Brain Compute... [more] | SP2019-29 WIT2019-28 pp.69-73 |
| EA, ASJ-H | 2019-08-09 10:30 |
Miyagi | Tohoku Univ. | Study on Robust Method for Blindly Estimating Speech Transmission Index using Convolutional Neural Network with Temporal Amplitude Envelope Suradej Doungpummet (JAIST), Jessada Karunjana (NASDA), Waree Kongprawechnon (SIIT), Masashi Unoki (JAIST) EA2019-30 |
We have developed a robust scheme for blindly estimating speech transmission index (STI) in noisy reverberant environmen... [more] | EA2019-30 pp.47-52 |
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