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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Improving training recipe of Remixed2Remixed for speech enhancement Li Li, Shogo Seki (CyberAgent)  EA2023-95 SIP2023-142 SP2023-77 |
In the use of deep learning for speech enhancement, supervised learning models that use pairs of clean speech and artifi... [more] | EA2023-95 SIP2023-142 SP2023-77 pp.202-207 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-02-28 13:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
[Invited Talk]
Multichannel audio source separation based on deep generative model and signal independence Li Li (CA) EA2022-88 SIP2022-132 SP2022-52 |
[more] | EA2022-88 SIP2022-132 SP2022-52 p.77 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-01 14:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Target speaker extraction based on conditional variational autoencoder and directional information in underdetermined condition Rui Wang, Li Li, Tomoki Toda (Nagoya Univ) EA2021-76 SIP2021-103 SP2021-61 |
This paper deals with a dual-channel target speaker extraction problem in underdetermined conditions. A blind source sep... [more] | EA2021-76 SIP2021-103 SP2021-61 pp.76-81 |
| EA | 2019-12-13 13:00 |
Fukuoka | Kyushu Inst. Tech. | Speaker-independent source separation with multichannel variational autoencoder Li Li (Univ. Tsukuba), Hirokazu Kameoka (NTT), Shota Inoue, Shoji Makino (Univ. Tsukuba) EA2019-77 |
The multichannel variational autoencoder method (MVAE) is a recently proposed determined source separation method, which... [more] | EA2019-77 pp.79-84 |
| EA, SIP, SP | 2019-03-14 13:30 |
Nagasaki | i+Land nagasaki (Nagasaki-shi) | [Poster Presentation]
Voice activity detection under high levels of noise using gated convolutional neural networks Li Li, Koshino Yuki, Matsumoto Mitsuo, Makino Shoji (Univ. Tsukuba) EA2018-102 SIP2018-108 SP2018-64 |
This paper deals with voice activity detection (VAD) tasks under high-level noise environments where signal-to-noise rat... [more] | EA2018-102 SIP2018-108 SP2018-64 pp.19-24 |
| EA, SIP, SP | 2019-03-15 13:30 |
Nagasaki | i+Land nagasaki (Nagasaki-shi) | [Poster Presentation]
An Evaluation of Underdetermined Source Separation Based on Multichannel Variational Autoencoder Shogo Seki (Nagoya Univ.), Hirokazu Kameoka (NTT), Li Li (Univ. Tsukuba), Tomoki Toda, Kazuya Takeda (Nagoya Univ.) EA2018-154 SIP2018-160 SP2018-116 |
This paper deals with a multichannel audio source separation problem under underdetermined conditions. Multichannel Non-... [more] | EA2018-154 SIP2018-160 SP2018-116 pp.323-328 |
| SP | 2016-08-24 16:15 |
Kyoto | ACCMS, Kyoto Univ. | [Poster Presentation]
Joint Enhancement of Spectral and Cepstral Sequences of Noisy Speech Li Li (Univ.Tsukuba), Hirokazu Kameoka, Takuya Higuchi (NTT), Hiroshi Saruwatari (Univ.Tokyo), Shoji Makino (Univ.Tsukuba) SP2016-32 |
While spectral domain speech enhancement algorithms using non-negative matrix factorization (NMF) are powerful in terms ... [more] | SP2016-32 pp.29-32 |
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