| 2025 | ICASSP | Sound Source Distance Estimation Utilizing Physics-informed Prior for Sound Event Localization and Detection. | Nao Sato, Masahiro Yasuda, Shoichiro Saito, Noboru Harada |
| 2025 | ICASSP | Spatial Annotation-free Training for Sound Event Localization and Detection. | Masahiro Yasuda, Shoichiro Saito, Nao Sato, Noboru Harada |
| 2024 | ICASSP | Online Target Sound Extraction with Knowledge Distillation from Partially Non-Causal Teacher. | Keigo Wakayama, Tsubasa Ochiai, Marc Delcroix, Masahiro Yasuda, Shoichiro Saito, Shoko Araki, Akira Nakayama |
| 2024 | ICASSP | 6DoF SELD: Sound Event Localization and Detection Using Microphones and Motion Tracking Sensors on Self-Motioning Human. | Masahiro Yasuda, Shoichiro Saito, Akira Nakayama, Noboru Harada |
| 2022 | ICASSP | Wearable Seld Dataset: Dataset For Sound Event Localization And Detection Using Wearable Devices Around Head. | Kento Nagatomo, Masahiro Yasuda, Kohei Yatabe, Shoichiro Saito, Yasuhiro Oikawa |
| 2022 | ICASSP | CNN-Transformer with Self-Attention Network for Sound Event Detection. | Keigo Wakayama, Shoichiro Saito |
| 2022 | ICASSP | Echo-Aware Adaptation of Sound Event Localization and Detection in Unknown Environments. | Masahiro Yasuda, Yasunori Ohishi, Shoichiro Saito |
| 2022 | ICASSP | Multi-View And Multi-Modal Event Detection Utilizing Transformer-Based Multi-Sensor Fusion. | Masahiro Yasuda, Yasunori Ohishi, Shoichiro Saito, Noboru Harada |
| 2020 | ICASSP | SPIDERnet: Attention Network For One-Shot Anomaly Detection In Sounds. | Yuma Koizumi, Masahiro Yasuda, Shin Murata, Shoichiro Saito, Hisashi Uematsu, Noboru Harada |
| 2020 | ICASSP | Sound Event Localization Based on Sound Intensity Vector Refined by Dnn-Based Denoising and Source Separation. | Masahiro Yasuda, Yuma Koizumi, Shoichiro Saito, Hisashi Uematsu, Keisuke Imoto |
| 2020 | Interspeech | A Transformer-Based Audio Captioning Model with Keyword Estimation. | Yuma Koizumi, Ryo Masumura, Kyosuke Nishida, Masahiro Yasuda, Shoichiro Saito |
| 2019 | ICASSP | SNIPER: Few-shot Learning for Anomaly Detection to Minimize False-negative Rate with Ensured True-positive Rate. | Yuma Koizumi, Shin Murata, Noboru Harada, Shoichiro Saito, Hisashi Uematsu |