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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| EA | 2024-05-22 13:50 |
Online | Online | Determined BSS based on the proximal average of IVA and DNNs Kazuki Matsumoto (Waseda Univ.), Koki Yamada, Kohei Yatabe (TUAT) |
(To be available after the conference date) [more] | |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 09:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Derivation of Direct Update Rule for Back-Projected Separation Matrix Yui Kuriki, Taishi Nakashima, Nobutaka Ono (TMU)  EA2023-66 SIP2023-113 SP2023-48 |
Blind source separation (BSS) is a widely used technique for separating mixed signals originating from multiple sources.... [more] | EA2023-66 SIP2023-113 SP2023-48 pp.31-36 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 10:10 |
Okinawa | (Primary: On-site, Secondary: Online) |
Analysis of Overlapped Utterances in Everyday Conversation and Source Separation by Online Independent Vector Analysis for Asynchronous Distributed Recordings Haruki Nammoku, Taishi Nakashima, Kouei Yamaoka, Yukoh Wakabayashi, Nobutaka Ono (TMU) EA2023-67 SIP2023-114 SP2023-49 |
In this study, we investigate the effects of overlapped utterances on transcription in everyday conversation and propose... [more] | EA2023-67 SIP2023-114 SP2023-49 pp.37-42 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 10:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Accelerating and stabilizing vectorwise coordinate descent for spatially regularized independent low-rank matrix analysis Yuto Ishikawa, Takuya Okubo, Norihiro Takamune (UTokyo), Tomohiko Nakamura (AIST), Daichi Kitamura (NIT Kagawa), Hiroshi Saruwatari (UTokyo), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2023-68 SIP2023-115 SP2023-50 |
Spatially regularized independent low-rank matrix analysis (SR-ILRMA) is the method that introduces the spatial prior in... [more] | EA2023-68 SIP2023-115 SP2023-50 pp.43-50 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 16:20 |
Okinawa | (Primary: On-site, Secondary: Online) |
Comparison of DNN architectures for determined BSS by proximal average of IVA and DNN Kazuki Matsumoto (Waseda Univ.), Koki Yamada, Kohei Yatabe (TUAT) EA2023-88 SIP2023-135 SP2023-70 |
We have proposed a framework called PA-BSS for high-performance separation matrix estimation using deep denoisers based ... [more] | EA2023-88 SIP2023-135 SP2023-70 pp.162-167 |
| EA, US (Joint) |
2023-12-22 13:00 |
Fukuoka | [Poster Presentation]
Multichannel Blind Source Separation Using Independent Low-Rank Matrix Analysis with Observed-Signal-Dependent Regularization Based on Spectrogram Consistency Takaaki Kojima, Norihiro Takamune, Sota Misawa (UTokyo), Daichi Kitamura (NIT,Kagawa), Hiroshi Saruwatari (UTokyo) EA2023-51 |
Independent low-rank matrix analysis (ILRMA) is the state-of-the-art technique for blind source separation under the ove... [more] | EA2023-51 pp.13-20 |
|
| EMM | 2023-03-02 14:30 |
Nagasaki | Fukue culture hall (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Watermark Extraction Method Using BSS
-- Improving Image Quality Using Inter-frame Difference -- Nao Harada, Rinka Kawano, Masaki Kawamura (Yamaguchi Univ.) EMM2022-80 |
To improve the quality of stego-videos, we consider embedding method of watermarks in blocks where the differences betwe... [more] | EMM2022-80 pp.66-71 |
| SIS | 2023-03-02 11:00 |
Chiba | Chiba Institute of Technology (Primary: On-site, Secondary: Online) |
Blink detection from one-dimensional face signal by using convolutional sparse dictionary learning Souichiro Maruyama, Makoto Nakashizuka (CIT) SIS2022-40 |
In this report, a blink detection method from average intensities of whole facial videos using convolutional dictionary... [more] | SIS2022-40 pp.1-4 |
| CAS, CS | 2023-03-01 10:20 |
Fukuoka | Kitakyushu International Conference Center (Primary: On-site, Secondary: Online) |
Approximate joint diagonalization for blind separation of superimposed images Shinya Saito, Kunio Oishi (Tokyo University of Tech.) CAS2022-98 CS2022-75 |
This report presents blind separation of superimposed images. When we take a picture for panorama thought window glass a... [more] | CAS2022-98 CS2022-75 pp.12-17 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 09:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Regularization Term Design Based on Spectrogram Consistency in Independent Low-Rank Matrix Analysis for Multichannel Audio Source Separation Sota Misawa, Norihiro Takamune (UTokyo), Kohei Yatabe (TUAT), Daichi Kitamura (NIT, Kagawa), Hiroshi Saruwatari (UTokyo) EA2022-105 SIP2022-149 SP2022-69 |
It is known that block permutation occurs in the separated signals obtained by independent low-rank matrix analysis. Rec... [more] | EA2022-105 SIP2022-149 SP2022-69 pp.177-184 |
| EA, US (Joint) |
2022-12-23 09:00 |
Hiroshima | Satellite Campus Hiroshima | Proposal of Speech Decomposition Algorithm by Cepstral-Basis-Decomposed Nonnegative Matrix Factorization and Application to Speech Source Separation Technique Fuga Oshima, Masashi Nakayama (Hiroshima City) EA2022-69 |
Nonnegative matrix factorization (NMF) is the algorithm that effectively represents acoustical signals by inputting ampl... [more] | EA2022-69 pp.49-54 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-17 15:00 |
Online | Online | Blind Source Separation based on Independent Low-Rank Matrix Analysis using Restricted Boltzmann Machines Shotaro Furuta, Takuya Kishida, Toru Nakashika (UEC) SP2022-8 |
In this paper, we propose a new blind source separation method that combines independent low-rank source separation (ILR... [more] | SP2022-8 pp.26-29 |
| 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 | 2022-05-13 13:10 |
Online | Online | Fast Blind Source Separation in Noisy Reverberant Environments Using Independent Vector Extraction Rintaro Ikeshita, Tomohiro Nakatani (NTT) EA2022-5 |
Blind source separation (BSS) is a technique of separating and extracting individual source signals only from their mixt... [more] | EA2022-5 pp.20-25 |
| EA | 2022-05-13 16:50 |
Online | Online | Basic study for permutation solver based on deep neural networks Fumiya Hasuike, Rui Watanabe, Daichi Kitamura (NIT, Kagawa) EA2022-13 |
This paper focuses on a permutation problem associated with frequency-domain independent component analysis (FDICA) that... [more] | EA2022-13 pp.62-67 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 10:55 |
Online | Online | Fetal Heart Rate Detection via Maternal ECG Cancellation by Neural-Network Autoencoder Abuzar Ahmad Qureshi, Lu Wang, Tomoaki Ohtsuki (Keio Univ.), Kazunari Owada, Hayato Hayashi (Atom Medical Co.) NLP2021-123 MICT2021-98 MBE2021-84 |
Fetal heart rate (HR) monitoring is necessary for accessing the state of the fetus during pregnancy and labor. Non-invas... [more] | NLP2021-123 MICT2021-98 MBE2021-84 pp.243-247 |
| RCS, SIP, IT | 2022-01-21 11:45 |
Online | Online | Simultaneous matrix diagonalization using alternating least-squares algorithm Shinya Saito, Kunio Oishi (Tokyo University of Tech.) IT2021-73 SIP2021-81 RCS2021-241 |
This paper presents an approach for overdetermined blind source separation (BSS) using AJD. The approach is constructed ... [more] | IT2021-73 SIP2021-81 RCS2021-241 pp.252-257 |
| ITE-ME, EMM, IE, LOIS, IEE-CMN, IPSJ-AVM [detail] | 2021-08-25 13:25 |
Online | Online | Extraction of watermarks from video frames by using BSS Akane Yokota, Masaki Kawamura (Yamaguchi Univ.) LOIS2021-17 IE2021-12 EMM2021-47 |
We propose a method for extracting watermarks additively embedded in video frames by using blind source separation (BS... [more] |
LOIS2021-17 IE2021-12 EMM2021-47 pp.7-12 |
| SIP | 2021-08-24 10:00 |
Online | Online | [Invited Talk]
Audio source separation based on independent low-rank matrix analysis and its extensions Daichi Kitamura (NIT Kagawa) SIP2021-32 |
Audio source separation is a technique for separating individual audio sources from an observed mixture signal. In parti... [more] | SIP2021-32 pp.19-24 |
| SIS, IPSJ-AVM | 2021-06-24 14:15 |
Online | Online | [Tutorial Lecture]
Noise Reduction using Nonnegative Matrix Factorization Motoaki Mour (Aichi Univ.) SIS2021-9 |
Nonnegative matrix factorization (NMF) is a general term for methods that factorize a matrix into two or more matrices w... [more] | SIS2021-9 pp.49-54 |
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