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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| HIP, HCS, HI-SIGCOASTER [detail] | 2024-05-13 13:20 |
Okinawa | Okinawa Industry Support Center | Strategies to encode non-speech sounds into language: A developmental study Kaede Hattori, Shoko Miyauchi, Kazuhide Hashiya (Kyushu Univ.)  HCS2024-12 HIP2024-12 |
To discover the progress in adapting phonology in the native language, the current study compared the strategies in verb... [more] | HCS2024-12 HIP2024-12 pp.57-60 |
| HIP, HCS, HI-SIGCOASTER [detail] | 2024-05-14 13:50 |
Okinawa | Okinawa Industry Support Center | Conditional Apologies in English
-- Speech-Act Theoretic Analysis and Examination Based on Sincerity Evaluation -- Akihiko Sakamoto (Tokyo Denki Univ.), Sachiko Takagi, Kevin M. McManus (Tokiwa Univ.) HCS2024-28 HIP2024-28 |
(To be available after the conference date) [more] | HCS2024-28 HIP2024-28 pp.147-152 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 16:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Multiple Lag Window Pairs for Estimation of Fundamental Frequency and Periodicity Measure Michiki Koshimori (UEC), Shigeki Sagayama (UTokyo/UEC), Toru Nakashika (UEC) EA2023-75 SIP2023-122 SP2023-57 |
Extending the main concept of modified autocorrelation method in LPC, we investigate lag windows, lag window pairs, and ... [more] | EA2023-75 SIP2023-122 SP2023-57 pp.85-90 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 10:40 |
Okinawa | (Primary: On-site, Secondary: Online) |
An Investigation into Weighting Strategies for Model Averaging in Continual Learning for Automatic Speech Recognition Kentaro Shinayama, Hiroshi Sato, Tomoharu Iwata, Takeshi Mori, Taichi Asami (NTT) EA2023-105 SIP2023-152 SP2023-87 |
In recent years, the application scope of speech recognition AI has expanded, enabling the acquisition of diverse data d... [more] | EA2023-105 SIP2023-152 SP2023-87 pp.262-267 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 16:35 |
Okinawa | (Primary: On-site, Secondary: Online) |
Evaluations of Multi-channel Blind Source Separation for Speech Recognition in Car Environments Yutsuki Takeuchi, Natsuki Ueno, Nobutaka Ono (Tokyo Metropolitan Univ.), Takashi Takazawa, Shuhei Shimanoe, Tomoki Tanemura (MIRISE Technologies) EA2023-127 SIP2023-174 SP2023-109 |
In car environments, speech recognition is difficult due to various types of noise. For this issue, speech enhancement b... [more] | EA2023-127 SIP2023-174 SP2023-109 pp.388-393 |
| SP, NLC, IPSJ-SLP, IPSJ-NL [detail] | 2023-12-03 11:05 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Enhancing Dysarthric Speech Recognition with Auxiliary Feature Fusion Module: Exploring Articulatory-related Features from Foundation Models Yuqin Lin, Longbiao Wang, Jianwu Dang (Tianjin Univ. & Univ. of Tokyo), Nobuaki Minematsu (Univ. of Tokyo) NLC2023-19 SP2023-39 |
Addressing dysarthric speech variability in Automatic Speech Recognition (ASR) is crucial for improving human-computer i... [more] | NLC2023-19 SP2023-39 pp.31-36 |
| ET | 2023-10-21 15:30 |
Nagano | Shinshu University Faculty of Engineering | "Listening" Performance of Generative AI and Elementary Foreign Language Learners in Code-Switching Discourse Sunaoka Kazuko (Waseda Univ.), Qin Xu (Kyoto Univ.) ET2023-23 |
We used the Whisper model to automatically recognize and process teachers' Japanese and Chinese code-switching (CS) in a... [more] | ET2023-23 pp.33-37 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2023-06-24 13:50 |
Tokyo | (Primary: On-site, Secondary: Online) |
Fast Neural Waveform Generation Model With Fully Connected Upsampling Haruki Yamashita (Kobe cniv/NICT), Takuma Okamoto (NICT), Ryoichi Takashima (Kobe Univ), Yamato Ohtani (NICT), Tetsuya Takiguchi (Kobe Univ), Tomoki Toda (Nagoya Univ/NICT), Hisashi Kawai (NICT) SP2023-15 |
In recent years, in text-to-speech synthesis, it is required to improve the inference speed while keeping the quality. ... [more] |
SP2023-15 pp.73-78 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-16 14:00 |
Okinawa | Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Analyzing Attractiveness of Cooking Recipe Titles based on Parts of Speech Nanami Takagi (Nagoya Univ.), Haruya Kyutoku (Aichi Univ. of Technology), Keisuke Doman (Chukyo Univ.), Yasutomo Kawanishi (RIKEN), Takatsugu Hirayama (Univ. of Human Environments), Takahiro Komamizu, Ichiro Ide (Nagoya Univ.) IMQ2022-59 IE2022-136 MVE2022-89 |
Recently, occasions to use recipe Websites is increasing, and also the number of users who publish their own cooking rec... [more] | IMQ2022-59 IE2022-136 MVE2022-89 pp.192-197 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-02-28 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
MS-FC-HiFiGAN : Fast Neural Waveform Generation Model With Learnable Lightweight Upsampling Haruki Yamashita (Kobe Univ/NICT), Takuma Okamoto (NICT), Ryoichi Takashima, Tetsuya Takiguchi (Kobe Univ), Tomoki Toda (Nagoya Univ/NICT), Hisashi Kawai (NICT) EA2022-76 SIP2022-120 SP2022-40 |
In recent years, in text-to-speech synthesis, it is required to improve the inference speed while keeping the quality. ... [more] |
EA2022-76 SIP2022-120 SP2022-40 pp.7-12 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 11:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
Analysis of Noisy-target Training for DNN-based speech enhancement and investigation towards its practical use Takuya Fujimura, Tomoki Toda (Nagoya Univ.) EA2022-112 SIP2022-156 SP2022-76 |
Deep neural network (DNN)-based speech enhancement usually uses a clean speech as a training target. However, it is hard... [more] | EA2022-112 SIP2022-156 SP2022-76 pp.221-226 |
| HCS | 2023-01-22 16:00 |
Kyoto | Kyoto Institute of Technology (Primary: On-site, Secondary: Online) |
Decoding of average ERPs during silent Japanese words by attention-based RNN with encoder-decoder Toshimasa Yamazaki, Yuko Tokunaga, Chieko Ito (KIT) HCS2022-74 |
This study attempted to decode average event-related potentials (ERPs) during silent Japanese words by attention-based r... [more] | HCS2022-74 pp.108-111 |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2022-11-30 16:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
Representing how it is said with what is said
-- Creation and analysis of an English corpus of focused speech and text reflecting paralinguistically expressed implications -- Naoaki Suzuki, Satoshi Nakamura (NAIST) NLC2022-15 SP2022-35 |
In speech communication, people convey intentions through what is said (linguistic information) and how it is said (para... [more] | NLC2022-15 SP2022-35 pp.33-38 |
| EA, EMM, ASJ-H | 2022-11-22 13:00 |
Online | Online | [Fellow Memorial Lecture]
Security and Privacy Preservation for Speech Signal
-- Approach from speech information hiding technology -- Masashi Unoki (JAIST) EA2022-60 EMM2022-60 |
Non-authentic but skillfully fabricated artificial replicas of authentic media in the real world are known as “media clo... [more] | EA2022-60 EMM2022-60 pp.99-104 |
| ET | 2022-11-05 15:20 |
Online | Online | Estimation and Visualization of Learning Types for Class Dialogues Using Neural Network Model Sakuei Onishi, Hiromitsu Shiina (Okayama Unisersity of Science), Tomohiko Yasumori (Okayama Univ. of Science) ET2022-38 |
In elementary school classes, lesson inspection activities have been conducted to improve classes, and feedback is impor... [more] | ET2022-38 pp.47-54 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-18 15:00 |
Online | Online | Improved speech analysis using F0-adaptive lag window Michiki Koshimori, Shigeki Sagayama, Takuya Kishida, Toru Nakashika (UEC) SP2022-21 |
The lag window method is based on a source-filter model, which separates the source information from the filter informat... [more] | SP2022-21 pp.90-93 |
| 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 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-02 10:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Evaluation of sentence-level generation in Japanese dialect speech synthesis using accent latent variables Kazuya Yufune, Tomoki Koriyama, Shinnosuke Takamichi, Hiroshi Saruwatari (UTokyo) EA2021-79 SIP2021-106 SP2021-64 |
Japanese dialect speech synthesis is useful for personalized speech synthesis systems. However, inability to prepare acc... [more] | EA2021-79 SIP2021-106 SP2021-64 pp.96-101 |
| IMQ, HIP | 2021-07-09 16:00 |
Online | Online | IMQ2021-5 HIP2021-20 |
To achieve emotional intensity estimation, we use segment-based estimation in which the utterance is divided into severa... [more] | IMQ2021-5 HIP2021-20 pp.17-22 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-18 13:00 |
Online | Online | F0 estimation of speech based on l2-norm regularized TV-CAR analysis Keiichi Funaki (Univ. of the Ryukyus) SP2021-2 |
Linear Prediction (LP) is the most successful speech analysis in speech processing, including speech coding implemented ... [more] |
SP2021-2 pp.7-12 |
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