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Technical Committee on Engineering Acoustics (EA) (Searched in: 2024)
Search Results: Keywords 'from:2024-05-22 to:2024-05-22'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| EA | 2024-05-22 13:00 |
Online | Online | Trends in Sound Source Separation and Enhancement at ICASSP2024 Yoshiki Masuyama (TMU)  EA2024-1 |
ICASSP 2024 was held in Seoul, South Korea, from April 14th to 19th. ICASSP is the IEEE Signal Processing Society's flag... [more] | EA2024-1 pp.1-6 |
| EA | 2024-05-22 13:25 |
Online | Online | EA2024-2 |
(To be available after the conference date) [more] | EA2024-2 pp.7-13 |
| 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) EA2024-3 |
Determined BSS separates source signals by applying the separation matrices, which are estimated under some assumption o... [more] | EA2024-3 pp.14-19 |
| 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 |
| EA | 2024-05-22 14:55 |
Online | Online | Environmental sound synthesis and creation of dataset using vocal imitations Yuki Okamoto (Ritsumeikan Univ.), Keisuke Imoto (Doshisha Univ.), Shinnosuke Takamichi (The Univ. of Tokyo/Keio Univ.), Ryotaro Nagase, Takahiro Fukumori, Yoichi Yamashita (Ritsumeikan Univ.) EA2024-5 |
One way to represent the characteristics of environmental sounds is to imitate the environmental sounds by human voice c... [more] | EA2024-5 p.22 |
| EA | 2024-05-22 15:20 |
Online | Online | Anomaly sound detection of industrial equipment using acoustical features related to timbral attribute Yasuji Ota, Ryoya Ogura, Masashi Unoki (JAIST) EA2024-6 |
In this paper, we proposed a method for detecting anomaly sound of industrial equipment based on timbre-related features... [more] | EA2024-6 pp.23-28 |
| EA | 2024-05-22 15:45 |
Online | Online | Audio-change Captioning to Explain Machine-sound Anomalies Shunsuke Tsubaki (Doshisha Univ./Hitachi), Yohei Kawaguchi, Tomoya Nishida (Hitachi), Keisuke Imoto (Doshisha Univ.), Yuki Okamoto (Ritsumeikan Univ./Hitachi), Kota Dohi, Takashi Endo (Hitachi) EA2024-7 |
[more] | EA2024-7 pp.29-33 |
| EA | 2024-05-22 16:10 |
Online | Online | Incremental Learning for Joint analysis of Acoustic Scenes and Sound Events Kaori Inoue, Yuka Fukumoto, Naoki Koga, Keisuke Imoto (Doshisha Univ.) EA2024-8 |
[more] | EA2024-8 pp.34-37 |
| EA | 2024-05-22 16:50 |
Online | Online | [Invited Talk]
Fundamentals of Diffusion-based Generative Models and their Application to Speech Enhancement and Separation Scheibler Robin (LY Corp.) EA2024-9 |
Diffusion models are a class of generative models that operate in an iterative manner, progressively transforming noise ... [more] | EA2024-9 p.38 |
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