Yuichiro Koyama

According to our database, Yuichiro Koyama authored at least 18 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Zero- and Few-shot Sound Event Localization and Detection.

Kazuki Shimada, Kengo Uchida, Yuichiro Koyama, Takashi Shibuya, Shusuke Takahashi, Yuki Mitsufuji, Tatsuya Kawahara

CoRR, 2023

Diffusion-Based Speech Enhancement with Joint Generative and Predictive Decoders.

Hao Shi, Kazuki Shimada, Masato Hirano, Takashi Shibuya, Yuichiro Koyama, Zhi Zhong, Shusuke Takahashi, Tatsuya Kawahara, Yuki Mitsufuji

CoRR, 2023

Diffusion-based Signal Refiner for Speech Separation.

Masato Hirano, Kazuki Shimada, Yuichiro Koyama, Shusuke Takahashi, Yuki Mitsufuji

CoRR, 2023

STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events.

Kazuki Shimada, Archontis Politis, Parthasaarathy Sudarsanam, Daniel Aleksander Krause, Kengo Uchida, Sharath Adavanne, Aapo Hakala, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Tuomas Virtanen, Yuki Mitsufuji

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Removing Distortion Effects in Music Using Deep Neural Networks.

Johannes Imort, Giorgio Fabbro, Marco A. Martínez Ramírez, Stefan Uhlich, Yuichiro Koyama, Yuki Mitsufuji

CoRR, 2022

Distortion Audio Effects: Learning How to Recover the Clean Signal.

Johannes Imort, Giorgio Fabbro, Marco A. Martínez Ramírez, Stefan Uhlich, Yuichiro Koyama, Yuki Mitsufuji

Proceedings of the 23rd International Society for Music Information Retrieval Conference, 2022

Multi-ACCDOA: Localizing And Detecting Overlapping Sounds From The Same Class With Auxiliary Duplicating Permutation Invariant Training.

Kazuki Shimada, Yuichiro Koyama, Shusuke Takahashi, Naoya Takahashi, Emiru Tsunoo, Yuki Mitsufuji

Proceedings of the IEEE International Conference on Acoustics, 2022

Spatial Mixup: Directional Loudness Modification as Data Augmentation for Sound Event Localization and Detection.

Ricardo Falcón Pérez, Kazuki Shimada, Yuichiro Koyama, Shusuke Takahashi, Yuki Mitsufuji

Proceedings of the IEEE International Conference on Acoustics, 2022

Spatial Data Augmentation with Simulated Room Impulse Responses for Sound Event Localization and Detection.

Yuichiro Koyama, Kazuhide Shigemi, Masafumi Takahashi, Kazuki Shimada, Naoya Takahashi, Emiru Tsunoo, Shusuke Takahashi, Yuki Mitsufuji

Proceedings of the IEEE International Conference on Acoustics, 2022

Music Source Separation With Deep Equilibrium Models.

Yuichiro Koyama, Naoki Murata, Stefan Uhlich, Giorgio Fabbro, Shusuke Takahashi, Yuki Mitsufuji

Proceedings of the IEEE International Conference on Acoustics, 2022

STARSS22: A Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events.

Archontis Politis, Kazuki Shimada, Parthasaarathy Sudarsanam, Sharath Adavanne, Daniel Krause, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Yuki Mitsufuji, Tuomas Virtanen

Proceedings of the 7th Workshop on Detection and Classification of Acoustic Scenes and Events 2022, 2022

2021

Ensemble of ACCDOA- and EINV2-based Systems with D3Nets and Impulse Response Simulation for Sound Event Localization and Detection.

Kazuki Shimada, Naoya Takahashi, Yuichiro Koyama, Shusuke Takahashi, Emiru Tsunoo, Masafumi Takahashi, Yuki Mitsufuji

CoRR, 2021

Accdoa: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization And Detection.

Kazuki Shimada, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi, Yuki Mitsufuji

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Exploring Optimal DNN Architecture for End-to-End Beamformers Based on Time-frequency References.

Yuichiro Koyama, Bhiksha Raj

CoRR, 2020

Efficient Integration of Multi-channel Information for Speaker-independent Speech Separation.

Yuichiro Koyama, Oluwafemi Azeez, Bhiksha Raj

CoRR, 2020

Exploring the Best Loss Function for DNN-Based Low-latency Speech Enhancement with Temporal Convolutional Networks.

Yuichiro Koyama, Tyler Vuong, Stefan Uhlich, Bhiksha Raj

CoRR, 2020

Metric Learning with Background Noise Class for Few-Shot Detection of Rare Sound Events.

Kazuki Shimada, Yuichiro Koyama, Akira Inoue

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

W-Net BF: DNN-based Beamformer Using Joint Training Approach.

Yuichiro Koyama, Bhiksha Raj

CoRR, 2019