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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-04 17:10 |
Online | Online | A Vocoder-free Any-to-Many Voice Conversion using Pre-trained vq-wav2vec Takeshi Koshizuka, Hidefumi Ohmura, Kouichi Katsurada (TUS)  EA2020-89 SIP2020-120 SP2020-54 |
Voice conversion (VC) is a technique that converts speaker-dependent non-linguistic information to another speaker's one... [more] | EA2020-89 SIP2020-120 SP2020-54 pp.176-181 |
| HCGSYMPO (2nd) |
2020-12-15 - 2020-12-17 |
Online | Online | Effects on Speakers' Behaviors in Speech Rate Converted Conversation by Keeping Constant of Listening Speed for Hearer Hiroyuki Oba, Tamami Mizuta, Hiroko Tokunaga, Naoki Mukawa, Hiroto Saito (Tokyo Denki Univ.) |
In this study, we evaluate the effects on speakers’ behaviors in speech rate converted conversation that keeps the liste... [more] | |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2020-12-03 16:50 |
Online | Online | Stabilize Fundamental Frequency of StarGAN based Voice Conversion Masashi Kimura (ConLab.), Hideyuki Kasuga (ZIKU) NLC2020-20 SP2020-23 |
Virtual Youtuber and Virtual Influencer is getting attention, which is video streamers with avator appearence createdcom... [more] | NLC2020-20 SP2020-23 pp.34-37 |
| WIT | 2020-06-12 13:30 |
Online | Online | Improving the pronounce clarity of dysarthric speech using CycleGAN Shuhei Imai, Takashi Nose, Aoi Kanagaki (Tohoku Univ.), Satoshi Watanabe (HTS), Akinori Ito (Tohoku Univ.) WIT2020-1 |
Several voice conversion systems have been developed that converts the dysarthric speech into healthy speech.The convent... [more] | WIT2020-1 pp.1-6 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Evaluation of vocal personality and expression for speech synthesized by non-parallel voice conversion with narrative speech Ryotaro Nagase, Keisuke Imoto, Ryosuke Yamanishi, Yoichi Yamashita (Ritsumeikan Univ.) EA2019-138 SIP2019-140 SP2019-87 |
In the technology of voice conversion, reproduction of emotion and intonation, pause is one of the research issues. Howe... [more] | EA2019-138 SIP2019-140 SP2019-87 pp.213-218 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Cross-Lingual Voice Conversion using Cyclic Variational Auto-encoder Hikaru Nakatani, Patrick Lumban Tobing, Kazuya Takeda, Tomoki Toda (Nagoya Univ.) EA2019-139 SIP2019-141 SP2019-88 |
In this report, we present a novel cross-lingual voice conversion (VC) method based on cyclic variational auto-encoder (... [more] | EA2019-139 SIP2019-141 SP2019-88 pp.219-224 |
| EA, SIP, SP | 2019-03-15 13:30 |
Nagasaki | i+Land nagasaki (Nagasaki-shi) | [Poster Presentation]
Robustness of statistical voice conversion based on waveform modification against external noise Yusuke Kurita, Kazuhiro Kobayashi, Kazuya Takeda (Nagoya Univ.), Tomoki Toda (Nagoya Univ./JST PRESTO) EA2018-153 SIP2018-159 SP2018-115 |
In this report, we investigate the statistical voice conversion (VC) under noisy environments. VC achieves conversion f... [more] |
EA2018-153 SIP2018-159 SP2018-115 pp.317-322 |
| SP | 2018-08-27 11:35 |
Kyoto | Kyoto Univ. | [Poster Presentation]
An Experimental Study on Transforming the Emotion in Speech using GAN Kenji Yasuda, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) SP2018-26 |
In domain transfer task deep learning has made it possible to generate more natural and highly accurate output. Especial... [more] | SP2018-26 pp.19-22 |
| AI | 2018-07-02 15:50 |
Hokkaido | Transforming the Emotion in Speech using CycleGAN Kenji Yasuda, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) AI2018-11 |
In domain transfer task deep learning makes it possible to generate more natural and highly accurate output. Especially ... [more] | AI2018-11 pp.61-66 |
|
| PRMU, SP | 2018-06-28 14:40 |
Nagano | Study of improving speech intelligibility for glossectomy patients via voice conversion with sound and lip movement. Seiya Ogino, Hiroki Murakami, Sunao Hara, Masanobu Abe (Okayama Univ.) PRMU2018-23 SP2018-3 |
In this paper, we propose the multimodal voice conversion based on Deep Neural Network using audio and lip movement info... [more] | PRMU2018-23 SP2018-3 pp.7-12 |
|
| PRMU, SP | 2018-06-28 15:10 |
Nagano | Multimodal voice conversion using deep bottleneck features and deep canonical correlation analysis Satoshi Tamura, Kento Horio, Hajime Endo, Satoru Hayamizu (Gifu Univ.), Tomoki Toda (Nagoya Univ.) PRMU2018-24 SP2018-4 |
In this paper, we aim at improving the speech quality in voice conversion and propose a novel multi-modal voice conversi... [more] | PRMU2018-24 SP2018-4 pp.13-18 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 10:25 |
Okinawa | Non-parallel and Many-to-Many Voice Conversion Using Variational Autoencoder Conditioned by Phonetic Posteriorgrams and d-vectors Yuki Saito (NTT/Univ. of Tokyo), Yusuke Ijima, Kyosuke Nishida (NTT), Shinnosuke Takamichi (Univ. of Tokyo) EA2017-105 SIP2017-114 SP2017-88 |
This paper proposes novel frameworks for non-parallel and many-to-many voice conversion (VC) using variational autoencod... [more] | EA2017-105 SIP2017-114 SP2017-88 pp.21-26 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-20 09:00 |
Okinawa | [Poster Presentation]
Development of NU Voice Conversion System 2018 Patrick Lumban Tobing, Yi-Chiao Wu, Tomoki Hayashi, Kazuhiro Kobayashi (Nagoya Univ.), Tomoki Toda (Nagoya Univ./JST PRESTO) EA2017-138 SIP2017-147 SP2017-121 |
This paper presents NU (Nagoya University) voice conversion (VC) system for the HUB task of Voice Conversion Challenge ... [more] |
EA2017-138 SIP2017-147 SP2017-121 pp.203-208 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-20 09:00 |
Okinawa | [Poster Presentation]
A Hybrid Approach on Electrolaryngeal Speech Enhancement based on Spectral Differential Features and Noise Suppression Mohammad Eshghi, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) EA2017-141 SIP2017-150 SP2017-124 |
This work presents a hybrid approach for enhancing the quality of the electrolaryngeal (EL) speech. Current hybrid enhan... [more] | EA2017-141 SIP2017-150 SP2017-124 pp.221-226 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-20 14:45 |
Okinawa | Development of NU non-parallel Voice Conversion System 2018 Yi-Chiao Wu, Patrick Lumban Tobing, Tomoki Hayashi, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) EA2017-172 SIP2017-181 SP2017-155 |
This paper introduces the NU non-parallel voice conversion (VC) system developed at Nagoya University for SPOKE task of ... [more] | EA2017-172 SIP2017-181 SP2017-155 pp.385-390 |
|
| SP, ASJ-H | 2018-01-20 13:50 |
Tokyo | The University of Tokyo | DNN Based Voice Conversion Method Considering Outputs of Multiple Networks Takuya Fujioka, Sun Qinghua (Hitachi) SP2017-68 |
In many conventional statistical voice conversion methods, the relations of source and target speech on all frames are e... [more] | SP2017-68 pp.11-15 |
| SP, ASJ-H | 2018-01-21 16:00 |
Tokyo | The University of Tokyo | A study on voice conversion based on WaveNet Jumpei Niwa, Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda (NIT) SP2017-84 |
This paper proposes a voice conversion technique based on WaveNet to directly generate target audio waveforms from acous... [more] | SP2017-84 pp.99-104 |
| SP, IPSJ-SLP (Joint) |
2017-07-27 14:30 |
Miyagi | Akiu Resort Hotel Crescent | [Invited Talk]
Synthesis, Recognition and Conversion of Various Speech Using Deep Learning and Their Applications Takashi Nose (Tohoku Univ.) SP2017-16 |
This paper focuses on synthesis, recognition and conversion of various speech in the speech processing using deep learni... [more] | SP2017-16 pp.3-8 |
| SP, IPSJ-SLP (Joint) |
2017-07-27 16:15 |
Miyagi | Akiu Resort Hotel Crescent | Voice Conversion Using Sequence-to-Sequence Learning of Context Posterior Probabilities and Evaluation of Dual Learning Hiroyuki Miyoshi, Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari (Univ. of Tokyo) SP2017-17 |
Voice conversion (VC) using sequence-to-sequence learning of context posterior probabilities is proposed. Conventional V... [more] | SP2017-17 pp.9-14 |
| SP | 2017-01-21 11:00 |
Tokyo | The University of Tokyo | [Poster Presentation]
A Study on Singer-Independent Singing Voice Conversion Using Read Speech Based on Neural Network Harunori Koike, Takashi Nose, Akinori Ito (Tohoku Univ.) SP2016-67 |
There is a problem that the conventional method requires the speech of the source speaker for training. We proposed a me... [more] | SP2016-67 pp.17-22 |
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