Zobrazeno 1 - 10
of 7 468
pro vyhledávání: '"A. Yatabe"'
We propose protocols for acquiring speech materials, making them reusable for future investigations, and presenting them for subjective experiments. We also provide means to evaluate existing speech materials' compatibility with target applications.
Externí odkaz:
http://arxiv.org/abs/2409.20516
Autor:
Matsumoto, Kazuki, Yatabe, Kohei
Solving the permutation problem is essential for determined blind source separation (BSS). Existing methods, such as independent vector analysis (IVA) and independent low-rank matrix analysis (ILRMA), tackle the permutation problem by modeling the co
Externí odkaz:
http://arxiv.org/abs/2409.09294
Autor:
Nakamura, Tomohiko, Yatabe, Kohei
This paper proposes a universal sound separation (USS) method capable of handling untrained sampling frequencies (SFs). The USS aims at separating arbitrary sources of different types and can be the key technique to realize a source separator that ca
Externí odkaz:
http://arxiv.org/abs/2309.12581
Autor:
Kawahara, Hideki, Yatabe, Kohei, Sakakibara, Ken-Ichi, Mizumachi, Mitsunori, Kitamura, Tatsuya
We introduce a general framework for measuring acoustic properties such as liner time-invariant (LTI) response, signal-dependent time-invariant (SDTI) component, and random and time-varying (RTV) component simultaneously using structured periodic tes
Externí odkaz:
http://arxiv.org/abs/2309.02767
Sparse time-frequency (T-F) representations have been an important research topic for more than several decades. Among them, optimization-based methods (in particular, extensions of basis pursuit) allow us to design the representations through object
Externí odkaz:
http://arxiv.org/abs/2308.01665
Publikováno v:
European Signal Processing Conference, Sep. 2023, pp. 326--330
In this paper, we propose algorithms for handling non-integer strides in sampling-frequency-independent (SFI) convolutional and transposed convolutional layers. The SFI layers have been developed for handling various sampling frequencies (SFs) by a s
Externí odkaz:
http://arxiv.org/abs/2306.10718
Autor:
Koizumi, Yuma, Zen, Heiga, Karita, Shigeki, Ding, Yifan, Yatabe, Kohei, Morioka, Nobuyuki, Bacchiani, Michiel, Zhang, Yu, Han, Wei, Bapna, Ankur
This paper introduces a new speech dataset called ``LibriTTS-R'' designed for text-to-speech (TTS) use. It is derived by applying speech restoration to the LibriTTS corpus, which consists of 585 hours of speech data at 24 kHz sampling rate from 2,456
Externí odkaz:
http://arxiv.org/abs/2305.18802
Autor:
Ken Asada, Syuzo Kaneko, Ken Takasawa, Kouya Shiraishi, Norio Shinkai, Yoko Shimada, Satoshi Takahashi, Hidenori Machino, Kazuma Kobayashi, Amina Bolatkan, Masaaki Komatsu, Masayoshi Yamada, Mototaka Miyake, Hirokazu Watanabe, Akiko Tateishi, Takaaki Mizuno, Yu Okubo, Masami Mukai, Tatsuya Yoshida, Yukihiro Yoshida, Hidehito Horinouchi, Shun-Ichi Watanabe, Yuichiro Ohe, Yasushi Yatabe, Takashi Kohno, Ryuji Hamamoto
Publikováno v:
Molecular Cancer, Vol 23, Iss 1, Pp 1-9 (2024)
Abstract Background The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS)
Externí odkaz:
https://doaj.org/article/5ca317bc30aa4ff796701baac2c9a5a6
Autor:
Eiji Nomura, Takatoshi Seki, Kentaro Yatabe, Hisamichi Yoshii, Hideki Izumi, Kazutake Okada, Hajime Kayano, Soichiro Yamamoto, Masaya Mukai, Hiroyasu Makuuchi
Publikováno v:
World Journal of Surgical Oncology, Vol 22, Iss 1, Pp 1-12 (2024)
Abstract Background Elderly gastric cancer patients (EGCPs) require treatment according to not just the stage of their cancer, but also to their general condition and organ function, and rather than full treatment, the appropriate amount of treatment
Externí odkaz:
https://doaj.org/article/005684783b1142c7acbd2c3034ce9c59
Autor:
Koizumi, Yuma, Zen, Heiga, Karita, Shigeki, Ding, Yifan, Yatabe, Kohei, Morioka, Nobuyuki, Zhang, Yu, Han, Wei, Bapna, Ankur, Bacchiani, Michiel
Speech restoration (SR) is a task of converting degraded speech signals into high-quality ones. In this study, we propose a robust SR model called Miipher, and apply Miipher to a new SR application: increasing the amount of high-quality training data
Externí odkaz:
http://arxiv.org/abs/2303.01664