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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] | 2024-02-29 09:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Pseudo-speaker augmentation based on vocal tract length perturbation considering speaker variability for speaker verification Fumika Ono, Tomoka Wakamatsu, Sayaka Shiota (TMU)  EA2023-62 SIP2023-109 SP2023-44 |
In order to construct a reliable speaker verification system based on speaker embeddings, it is necessary to train the s... [more] | EA2023-62 SIP2023-109 SP2023-44 pp.7-12 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 10:10 |
Okinawa | (Primary: On-site, Secondary: Online) |
Noise-Robust Voice Conversion by Denoising Training Conditioned with Latent Variables of Speech Quality and Recording Environment Takuto Igarashi, Yuki Saito, Kentaro Seki, Shinnosuke Takamichi (UT), Ryuichi Yamamoto, Kentaro Tachibana (LY), Hiroshi Saruwatari (UT) EA2023-63 SIP2023-110 SP2023-45 |
In this paper, we propose noise-robust voice conversion by conditioning latent variables representing speech quality and... [more] | EA2023-63 SIP2023-110 SP2023-45 pp.13-18 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Multi-Dialect Speech Synthesis with Interpretable Accent latent Variable based on VQ-VAE Kazuki Yamauchi, Yuki Saito, Hiroshi Saruwatari (UTokyo) EA2023-98 SIP2023-145 SP2023-80 |
In this paper, we address two tasks: "Intra-dialect Text-to-Speech (TTS)," aiming to synthesize speech in the same diale... [more] | EA2023-98 SIP2023-145 SP2023-80 pp.220-225 |
| EMM | 2024-01-16 14:50 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Development of Smartphone App of an application of EmoEditor (Emotion-Expressive Editor) to mail communications Yuki Shimamura, Michiharu Niimi (KIT) EMM2023-82 |
We report the implementation of an emotion-expressive editor, EmoEditor, which enables emotion expression through font c... [more] | EMM2023-82 pp.13-18 |
| LOIS, SITE, ISEC | 2023-11-10 12:10 |
Hiroshima | Satellite Campus Hiroshima (Primary: On-site, Secondary: Online) |
Zero-Knowledge Proofs for ownership of Deep Neural Network Shungo Sato, Hidema Tanaka (NDA) ISEC2023-67 SITE2023-61 LOIS2023-25 |
Because AI technologies have rapidly spread and developed in our society, Neural Networks, which are one of Machine Lear... [more] | ISEC2023-67 SITE2023-61 LOIS2023-25 pp.86-92 |
| NS | 2023-04-13 13:40 |
Fukushima | Nihon University, Koriyama Campus + Online (Primary: On-site, Secondary: Online) |
Vehicle Traffic Density Estimation for Predicting Communication Traffic Volume by Vehicle Communication Service Yoshie Morita, Kengo Tajiri, Yoichi Matsuo (NTT) NS2023-3 |
Vehicle communication services are new services using the mobile communication network. Since these services are expecte... [more] | NS2023-3 pp.13-18 |
| SS | 2023-03-15 13:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Improvement of Encoding and Ablation Methods in Fault Localization by Ablation Takuma Ikeda, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2022-67 |
Spectrum-based Fault Localization (SFL) is a technique to locate faults in source code using execution traces. A method ... [more] | SS2022-67 pp.121-126 |
| IA, ICSS | 2022-06-24 10:25 |
Nagasaki | Univ. of Nagasaki (Primary: On-site, Secondary: Online) |
Application of Adversarial Examples to Physical ECG Signals Taiga Ono (Waseda Univ.), Takeshi Sugawara (UEC), Jun Sakuma (Tsukuba Univ./RIKEN), Tatsuya Mori (Waseda Univ./RIKEN/NICT) IA2022-11 ICSS2022-11 |
This work aims to assess the reality and feasibility of applying adversarial examples to attack cardiac diagnosis system... [more] | IA2022-11 ICSS2022-11 pp.61-66 |
| KBSE | 2022-03-10 10:15 |
Online | Online (Zoom) | Safety risk analysis and evaluation method for DNN system in autonomous driving Tomoko Kaneko, Yuji Takahashi (NII), Shinichi Yamaguchi (SDM), Junji Hashimoto (GREE), Nobukazu Yoshioka (Soudai) KBSE2021-51 |
There is a great concern about the quality of current AI, especially DNN (deep learning), especially about its safety an... [more] | KBSE2021-51 pp.60-65 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 09:20 |
Online | Online | Block Sparse MLP-based Vision DNN Accelerators on Embedded FPGAs Akira Jinguji, Hiroki Nakahara (Tokyo Tech) VLD2021-21 ICD2021-31 DC2021-27 RECONF2021-29 |
Since the advent of Vision Transformer, a deep learning model for image recognition without Convolution, MLP-based model... [more] | VLD2021-21 ICD2021-31 DC2021-27 RECONF2021-29 pp.25-30 |
| EMM, EA, ASJ-H | 2021-11-15 09:00 |
Online | Online | [Poster Presentation]
A Study on Convergency of DNN Watermarking without Embedding Loss Function Takuro Tanaka, Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) EA2021-35 EMM2021-62 |
Intellectual Property Rights protection related to Deep Neural Networks is an important issue due to the high cost of tr... [more] | EA2021-35 EMM2021-62 pp.49-54 |
| RISING (3rd) |
2021-11-16 11:30 |
Tokyo | (Primary: On-site, Secondary: Online) |
Throughput Prediction by Radio Environment Correlation Recognition Using Crowd Sensing and Federated Learning Satoshi Nakaniida, Takeo Fujii (UEC) |
We propose an approach using federated learning for predicting Wi-Fi and LTE transmission control protocol (TCP) through... [more] | |
| SR | 2021-11-05 11:15 |
Online | Online | Throughput Prediction by Radio Environment Correlation Recognition Using Crowd Sensing and Federated Learning Satoshi Nakaniida, Takeo Fujii (UEC) SR2021-53 |
We propose an approach using federated learning for predicting Wi-Fi and LTE transmission control protocol (TCP) through... [more] | SR2021-53 pp.72-78 |
| SP, WIT, IPSJ-SLP, ASJ-H [detail] | 2021-10-19 15:10 |
Online | Online | A study on model training for DNN-HSMM-based speech synthesis using a large-scale speech corpus Nobuyuki Nishizawa, Gen Hattori (KDDI Research) SP2021-34 WIT2021-27 |
In this study, an investigation into model training for DNN-HSMM-based speech synthesis using a large speech corpus coll... [more] | SP2021-34 WIT2021-27 pp.52-57 |
| PRMU, IPSJ-CVIM | 2020-05-14 13:30 |
Online | Online | Human Action Recognition with Two-stream 3D BagNet Junya Uchida, Yu Wang, Jien Kato (Ritsumeikan Univ.) PRMU2020-3 |
We propose the Two-stream 3D BagNet for the human action recognition task. The proposed architecture is inspired by the ... [more] | PRMU2020-3 pp.13-17 |
| PRMU, IPSJ-CVIM | 2020-03-17 16:00 |
Kyoto | (Cancelled but technical report was issued) |
Acceleration of Deep Learning Inference by Model Cascading Shohei Enomoto, Takeharu Eda (NTT) PRMU2019-98 |
In recent years, various applications have appeared due to the development of deep learning and the spread of IoT device... [more] | PRMU2019-98 pp.203-208 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-06 10:10 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
A Comparison Study of Neural Sign Language Translation Methods with Spatio-Temporal Features Kodai Watanabe, Wataru Kameyama (Waseda Univ.) IMQ2019-68 IE2019-150 MVE2019-89 |
In Neural Sign Language Translation, a model based on 2DCNN (2 Dimensional Convolutional Neural Network) called AlexNet ... [more] | IMQ2019-68 IE2019-150 MVE2019-89 pp.273-278 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
[Poster Presentation]
Automatic estimation of prosodic control made in English utterances using DNN-based acoustic models trained with prosodic features and labels Yang Shen, Shintarou Ando, Nobuaki Minematsu, Daisuke Saito (UTokyo), Satoshi Kobashikawa (NTT) EA2019-136 SIP2019-138 SP2019-85 |
This paper investigate how to utilize DNN acoustic models trained with prosodic features and labels to detect prosodic e... [more] | EA2019-136 SIP2019-138 SP2019-85 pp.201-206 |
| NLC, IPSJ-NL, SP, IPSJ-SLP (Joint) [detail] |
2019-12-06 16:00 |
Tokyo | NHK Science & Technology Research Labs. | A comparison of neural vocoders in singing voice synthesis Sota Wada, Yukiya Hono, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda (Nagoya Inst. of Tech.) SP2019-42 |
In this study, we compare five types of vocoders based on neural networks (neural vocoders) for singing voice synthesis.... [more] | SP2019-42 pp.85-90 |
| SP | 2019-06-13 13:30 |
Kanagawa | Tokyo Institute of Technology | A study on style transplantation modeling techniques for DNN-based speech synthesis Yoshiki Hiruta (Tokyo Tech), Tomoki Koriyama (The Univ. of Tokyo), Yuuki Tachioka (Denso IT Lab), Takao Kobayashi (Tokyo Tech) SP2019-1 |
This paper investigates style transplantation modeling techniques for DNN-based statistical parametric speech synthesis.... [more] | SP2019-1 pp.1-6 |
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