A study on a digital watermarking technique for music data using distortion effect. - Yuto Matsunaga; Tetsuya Kojima; Naofumi Aoki; Yoshinori Dobashi; Tsuyoshi Yamamoto (IWSDA, 2017)

A Digital Modeling Technique for Distortion Effect Based on a Machine Learning Approach. - Yuto Matsunaga; Naofumi Aoki; Yoshinori Dobashi; Tsuyoshi Yamamoto (APSIPA, 2018)

Some Evaluations on a Digital Watermarking Technique for Music Data Using Distortion Effect. - Yuto Matsunaga; Tetsuya Kojima; Naofumi Aoki; Yoshinori Dobashi; Tsuyoshi Yamamoto (IEICE Trans. Inf. Syst., 2019)

A Black Box Modeling Technique for Distortion Stomp Boxes Using LSTM Neural Networks. - Yuto Matsunaga; Naofumi Aoki; Yoshinori Dobashi; Tetsuya Kojima (ICAIIC, 2020)

Distortion based Watermark Extraction Technique Using 1D CNN. - Yuto Matsunaga; Naofumi Aoki; Yoshinori Dobashi; Tetsuya Kojima (ICAIIC, 2021)

Prompt Tuning for Audio Deepfake Detection: Computationally Efficient Test-time Domain Adaptation with Limited Target Dataset. - Hideyuki Oiso; Yuto Matsunaga; Kazuya Kakizaki; Taiki Miyagawa (INTERSPEECH, 2024)

ConvFL: Efficient Federated Learning of Heterogeneous Model Structures with Converters. - Yuto Matsunaga; Satoru Momiyama; Batnyam Enkhtaivan; Taiki Miyagawa; Isamu Teranishi (SmartIoT, 2024)

MAFT: Multimodal Automated Fact-Checking via Textualization. - Kazuya Kakizaki; Yuto Matsunaga; Ryo Furukawa (AAAI, 2025)