Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SP, IPSJ-MUS, IPSJ-SLP [detail] |
2024-06-15 13:50 |
Tokyo |
(Primary: On-site, Secondary: Online) |
Acoustic-to-articulatory Inversion using real-time MRI for Pronunciation Practice Anna Oura, Hideaki Kikuchi, Tetsunori Kobayashi (Waseda Univ.) |
(To be available after the conference date) [more] |
|
EA |
2024-05-22 14:15 |
Online |
Online |
未定
-- 未定 -- Tsubasa Ochiai (NTT), Kazuma Iwamoto (Doshisha Univ.), Marc Delcroix, Rintaro Ikeshita, Hiroshi Sato, Shoko Araki (NTT), Shigeru Katagiri (Doshisha Univ.) EA2024-4 |
Deep learning techniques have dramatically improved the speech enhancement (SE) performance of single-channel SE. Howeve... [more] |
EA2024-4 pp.20-21 |
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 |
CAS, CS |
2024-03-14 13:30 |
Okinawa |
|
Characterization of Semantic Communications in Speech Signal Transmission Futo Iwanaga, Daisuke Umehara (Kyoto Inst. of Tech.) CAS2023-118 CS2023-111 |
In recent years, the volume of data in data communication has surged, Characterization of Semantic Communications in Spe... [more] |
CAS2023-118 CS2023-111 pp.41-46 |
SIP, SP, EA, IPSJ-SLP [detail] |
2024-03-01 10:40 |
Okinawa |
(Primary: On-site, Secondary: Online) |
An Investigation on the Speech Recovery from EEG Signals Using Transformer Tomoaki Mizuno (The Univ. of Electro-Communications), Takuya Kishida (Aichi Shukutoku Univ.), Natsue Yoshimura (Tokyo Tech), Toru Nakashika (The Univ. of Electro-Communications) EA2023-108 SIP2023-155 SP2023-90 |
Synthesizing full speech from ElectroEncephaloGraphy(EEG) signals is a challenging task. In this paper, speech reconstru... [more] |
EA2023-108 SIP2023-155 SP2023-90 pp.277-282 |
SIP, SP, EA, IPSJ-SLP [detail] |
2024-03-01 15:25 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Investigation of objective intelligibility metrics based on speech foundation models for Clarity Prediction Challenge 2 Katsuhiko Yamamoto (CyberAgent) EA2023-119 SIP2023-166 SP2023-101 |
Speech Foundation Models (SFMs), which use components like the encoder layer of Whisper, have been suggested to separate... [more] |
EA2023-119 SIP2023-166 SP2023-101 pp.334-339 |
EA, ASJ-H, ASJ-MA, ASJ-SP |
2023-07-02 15:10 |
Hokkaido |
|
Speech Restoration of Spectrogram Images Printed in a Document "Visible Speech" Published in 1947 Naofumi Aoki (Hokkaido Univ.) EA2023-6 |
The restoration of speech materials recorded in the past might be regarded as a study in acoustical archeology. It may p... [more] |
EA2023-6 pp.12-15 |
HIP, HCS, HI-SIGCOASTER [detail] |
2023-05-15 10:20 |
Okinawa |
Okinawa Industry Support Center (Primary: On-site, Secondary: Online) |
Cognitive Load Estimation of Speech-in-Noise Recall Task with State-Space Models Mateusz Dubiel (uni.lu), Minoru Nakayama (Tokyo Tech.), Xin Wang (NII) HCS2023-7 HIP2023-7 |
Cognitive workload during a listening and recall task was estimated using a state-space model based on metrics of pupill... [more] |
HCS2023-7 HIP2023-7 pp.29-32 |
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 |
SP, IPSJ-SLP, EA, SIP [detail] |
2023-02-28 13:00 |
Okinawa |
(Primary: On-site, Secondary: Online) |
[Invited Talk]
Multiple sound spot synthesis meets multilingual speech synthesis
-- Implementation is really all we need -- Takuma Okamoto (NICT) EA2022-87 SIP2022-131 SP2022-51 |
A multilingual multiple sound spot synthesis system is implemented as a user interface for real-time speech translation ... [more] |
EA2022-87 SIP2022-131 SP2022-51 pp.73-76 |
HCGSYMPO (2nd) |
2022-12-14 - 2022-12-16 |
Kagawa |
Onsite (Sunport Takamatsu) and Online (Primary: On-site, Secondary: Online) |
Modelling cognitive load with ocular responses during a noisy synthetic speech recall task Mateusz Dubiel (uni.lu), Minoru Nakayama (Tokyo Tech.), Xin Wang (NII) |
We applied state-space models to estimate the cognitive workload based
on participants' reactions to speech signals (i... [more] |
|
EA, EMM, ASJ-H |
2022-11-22 13:00 |
Online |
Online |
[Fellow Memorial Lecture]
Security and Privacy Preservation for Speech Signal
-- Approach from speech information hiding technology -- Masashi Unoki (JAIST) EA2022-60 EMM2022-60 |
Non-authentic but skillfully fabricated artificial replicas of authentic media in the real world are known as “media clo... [more] |
EA2022-60 EMM2022-60 pp.99-104 |
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 |
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 |
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 |
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 |
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 09:20 |
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 |