Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Yuki MITSUFUJI"'
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-19 (2024)
Abstract This paper presents the crossing scheme (X-scheme) for improving the performance of deep neural network (DNN)-based music source separation (MSS) with almost no increasing calculation cost. It consists of three components: (i) multi-domain l
Externí odkaz:
https://doaj.org/article/4cb69dcbfae44923b88de1070dc8e3a1
Autor:
Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai, Woosung Choi, Marco Martínez-Ramírez, Weihsiang Liao, Igor Gadelha, Geraldo Ramos, Eddie Hsu, Hugo Rodrigues, Fabian-Robert Stöter, Alexandre Défossez, Yi Luo, Jianwei Yu, Dipam Chakraborty, Sharada Mohanty, Roman Solovyev, Alexander Stempkovskiy, Tatiana Habruseva, Nabarun Goswami, Tatsuya Harada, Minseok Kim, Jun Hyung Lee, Yuanliang Dong, Xinran Zhang, Jiafeng Liu, Yuki Mitsufuji
Publikováno v:
Transactions of the International Society for Music Information Retrieval, Vol 7, Iss 1, Pp 63–84-63–84 (2024)
This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX’23). We provide a summary of the challenge setup and introduce the task of robust music source separation (MSS), i.e., training MSS models in the presence of
Externí odkaz:
https://doaj.org/article/a4ee59ff957d4d27b2b7ec70bfd0d657
Autor:
Stefan Uhlich, Giorgio Fabbro, Masato Hirano, Shusuke Takahashi, Gordon Wichern, Jonathan Le Roux, Dipam Chakraborty, Sharada Mohanty, Kai Li, Yi Luo, Jianwei Yu, Rongzhi Gu, Roman Solovyev, Alexander Stempkovskiy, Tatiana Habruseva, Mikhail Sukhovei, Yuki Mitsufuji
Publikováno v:
Transactions of the International Society for Music Information Retrieval, Vol 7, Iss 1, Pp 44–62-44–62 (2024)
This paper summarizes the cinematic demixing (CDX) track of the Sound Demixing Challenge 2023 (SDX’23). We provide a comprehensive summary of the challenge setup, detailing the structure of the competition and the datasets used. Especially, we deta
Externí odkaz:
https://doaj.org/article/4d5fad42081f45e48007f343da8811e3
Publikováno v:
International Society for Music Information Retrieval Conference Proceedings; 2023, p215-222, 8p
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 29:607-617
There is growing interest in new audio formats in the context of virtual reality (VR), and higher-order ambisonics (HOA) is preferred for VR systems to transmit recorded scenes owing to its transmission efficiency and its flexibility to work with dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad7baa061e879a8a2808fbe9695c78c2
https://doi.org/10.1109/taslp.2020.3045528
https://doi.org/10.1109/taslp.2020.3045528
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 28:656-670
Active acoustic noise attenuation over a sizable space is a challenging problem in signal processing. The noise attenuation performance of feedforward active noise control (ANC) relies on the preciseness of a reference signal of a primary noise field
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ae66731905fa014792aff2d0beabd49
https://doi.org/10.1109/taslp.2019.2962684
https://doi.org/10.1109/taslp.2019.2962684
Autor:
Norihiro Takamune, Stefan Uhlich, Hiroshi Saruwatari, Daichi Kitamura, Shoichi Koyama, Yuki Mitsufuji
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 28:49-60
Blind source separation exploiting multichannel information has long been a popular topic, and recently proposed methods based on the local Gaussian model have shown promising results despite its high computational cost for the case of many microphon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4e64f2d3e6b60733eac92348b1a2be4
https://doi.org/10.1109/taslp.2019.2948770
https://doi.org/10.1109/taslp.2019.2948770
Autor:
Yuki Mitsufuji, Giorgio Fabbro, Stefan Uhlich, Fabian-Robert Stöter, Alexandre Défossez, Minseok Kim, Woosung Choi, Chin-Yun Yu, Kin-Wai Cheuk
Publikováno v:
Frontiers in Signal Processing. 1
Music source separation has been intensively studied in the last decade and tremendous progress with the advent of deep learning could be observed. Evaluation campaigns such as MIREX or SiSEC connected state-of-the-art models and corresponding papers
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::738ac1be8da2f1134ed21bfbbc5e701a
https://doi.org/10.3389/frsip.2021.808395
https://doi.org/10.3389/frsip.2021.808395
Autor:
Koichi Saito, Naoki Murata, Toshimitsu Uesaka, Chieh-Hsin Lai, Yuhta Takida, Takao Fukui, Yuki Mitsufuji
Removing reverb from reverberant music is a necessary technique to clean up audio for downstream music manipulations. Reverberation of music contains two categories, natural reverb, and artificial reverb. Artificial reverb has a wider diversity than
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6dabaafe403c97a2c88b78fafd7f757
Autor:
Archontis Politis, Kazuki Shimada, Parthasaarathy Ariyakulam Sudarsanam, Sharath Adavanne, Daniel Krause, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Yuki Mitsufuji, Tuomas Oskari Virtanen
Publikováno v:
Tampere University
This report presents the Sony-TAu Realistic Spatial Soundscapes 2022 (STARS22) dataset for sound event localization and detection, comprised of spatial recordings of real scenes collected in various interiors of two different sites. The dataset is ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c127d04abc8ca3e8f6fdf8cad5e2a34e