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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 90  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
HCS 2022-08-27
15:15
Hyogo
(Primary: On-site, Secondary: Online)
A Study of Feedback Methods for Speakers in Speech Rate Converted Conversation -- Comparative evaluation for adaptive switching between audio feedback and visual feedback --
Kazuma Ban (Tokyo Denki Univ.), Hiroko Tokunaga (Tokyo Denki Univ./RIKEN), Naoki Mukawa, Hiroto Saito (Tokyo Denki Univ.) HCS2022-47
Speech rate conversion is a useful technique for people who need assistance in listening comprehension and non-native sp... [more] HCS2022-47
pp.61-66
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-13
14:50
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
Investigation of noise removal using U-Net and voice recognition performance improvement -- for train running noise --
Jian Lin, Shota Sano, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2022-26
A method for converting noisy sound into images to remove the noise has been proposed. We are attempting to remove train... [more] SeMI2022-26
pp.34-39
SP, IPSJ-MUS, IPSJ-SLP [detail] 2022-06-17
15:00
Online Online Study of End-to-End Text-to-Speech that can seamlessly control speaker's individuality by Manipulating Speaker features
Naoki Aotani, Sunao Hara, Msanobu Abe (Okayama Univ) SP2022-14
In this paper, we investigate an End-to-End speech synthesis scheme that enables to seamlessly control speaker individua... [more] SP2022-14
pp.55-60
SP, IPSJ-MUS, IPSJ-SLP [detail] 2022-06-18
10:50
Online Online [Invited Talk] Crazy vocoder is unbreakable -- But let's talk about an informal vision of the future --
Masanori Morise (Meiji Univ.) SP2022-15
When current speech synthesis researchers refer to Vocoder in their papers, they are most likely referring to Neural voc... [more] SP2022-15
pp.61-66
HCS 2022-03-12
10:10
Online Online Evaluation of Feedback Methods for Speakers in Speech Rate Converted Conversation
Tamami Mizuta, Hiroko Tokunaga, Naoki Mukawa, Hiroto Saito (Tokyo Denki Univ.) HCS2021-70
This study clarifies the characteristics of voice feedback and visual feedback, which are support functions for speakers ... [more] HCS2021-70
pp.55-60
WIT, IPSJ-AAC 2022-03-08
10:55
Online Online A study on high-intelligibility speech synthesis of dysarthric speakers using voice conversion from normal speech and multi-speaker vocoder
Tetsuro Takano (HTS), Takashi Nose, Aoi Kanagaki (Tohoku Univ.), Satoshi Watanabe (HTS) WIT2021-46
In this study, we investigated the possibility of generating intelligible synthetic speech by converting the voice of a ... [more] WIT2021-46
pp.18-23
EA, SIP, SP, IPSJ-SLP [detail] 2022-03-02
11:35
Okinawa
(Primary: On-site, Secondary: Online)
Study of Method for Improving Speech Intelligibility in Glossectomy Patients by Knowledge Distillation via Lip Features
Kazushi Takashima, Masanobu Abe, Sunao Hara (Okayama Univ.) EA2021-81 SIP2021-108 SP2021-66
In this paper, we propose a voice conversion method for improving speech intelligibility uttered by glossectomy patients... [more] EA2021-81 SIP2021-108 SP2021-66
pp.108-113
NLC, IPSJ-NL, SP, IPSJ-SLP [detail] 2021-12-03
10:30
Online Online An approach to voice conversion for manipulating emotion dimensions
Keita Mukada, Hiroki Mori (Utsunomiya Univ.) NLC2021-25 SP2021-46
We propose an emotional voice conversion method based on the emotion dimensions. Conventional emotional voice conversion... [more] NLC2021-25 SP2021-46
pp.39-41
SP, IPSJ-SLP, IPSJ-MUS 2021-06-19
15:00
Online Online Simulation of Body-conducted Speech and Synthesis of One's Own Voice with a Sound-proof Earmuff and Bone-conduction Microphones
Chen Ruiyan, Nishimura Tazuko, Minematsu Nobuaki, Saito Daisuke (UTokyo) SP2021-15
When one hears his/her recorded voices for the first time, s/he is probably surprised and not rarely disappointed at the... [more] SP2021-15
pp.63-68
SP, IPSJ-SLP, IPSJ-MUS 2021-06-19
15:00
Online Online Preliminary study on synthesizing relaxing voices -- from a perspective of recognized/evoked emotions and acoustic features --
Yuki Watanabe, Shuichi Sakamoto (Tohoku Univ.), Takayuki Hoshi, Yoshiki Nagatani, Manabu Nakano (Pixie Dust Technologies) SP2021-19
The goal of this study is to synthesize speech sound which induces relaxed emotion. As the preliminary study, we investi... [more] SP2021-19
pp.85-90
SP, IPSJ-SLP, IPSJ-MUS 2021-06-19
15:00
Online Online Unseen speaker's Voice Conversion by FaderNetVC with Speaker Feature Extractor
Takumi Isako, Takuya Kishida, Toru Nakashika (UEC) SP2021-20
In recent years, many voice conversion models using Deep Neural Network (DNN) have been proposed, and FaderNetVC is one ... [more] SP2021-20
pp.91-96
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
 Results 1 - 20 of 90  /  [Next]  
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