About Me个人简介

I am a doctoral student at Nakadai Lab, Institute of Science Tokyo. My research interests include speech/audio generative models, audio source separation, and spatial audio. I welcome collaborations ~ 🤖

我是东京科学大学 Nakadai Lab 的博士生。我的研究方向包括语音/音频生成模型、音源分离与空间音频等，欢迎合作~ 🤖

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Education教育背景

Institute of Science Tokyo, 东京科学大学（东京工业大学）， Ph.D. in Systems and Control Engineering 系统与控制工程，博士

Beihang University, 北京航空航天大学， M.S. in Vehicle Engineering 车辆工程，硕士

Jilin University, 吉林大学， B.Eng. in Vehicle Engineering 车辆工程，本科

Project项目

  • Unsupervised Single-Channel Audio Separation with Diffusion Source Priors

    Open-source implementation for the AAAI 2026 paper on unsupervised single-channel audio separation across speech-sound, sound-sound, and speech-speech mixtures.

    AAAI 2026 论文的开源实现，面向 speech-sound、sound-sound 与 speech-speech 等单通道音频分离任务。

    [Paper] [Code] [Demo]

  • Unsupervised Single-Channel Speech Separation with Diffusion under Speaker-Embedding Guidance

    Code for unsupervised single-channel speech separation with diffusion source models and speaker-embedding guidance.

    基于扩散源模型和说话人嵌入引导的无监督单通道语音分离代码。

    [Paper] [Code] [Demo]

  • Real Grid RIR Dataset

    A real room impulse response dataset collected at grid source locations in a meeting room, useful for distance estimation, spatial audio separation, and target extraction.

    会议室网格位置采集的真实房间脉冲响应数据集，适用于距离估计、空间音频分离和目标提取等研究。

    [Dataset] [Code]

Publication论文

  1. R. Shi, C. Li, J. Wang, et al. “Unsupervised Single-Channel Audio Separation with Diffusion Source Priors”. Proceedings of the AAAI Conference on Artificial Intelligence, 2026. [arXiv]
  2. R. Shi, B. Yen, and K. Nakadai. “Distance Based Single-Channel Target Speech Extraction”. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025. [arXiv]
  3. R. Shi, Z. Lin, B. Yen, et al. “Single-Channel Target Speech Extraction Utilizing Distance and Room Clues”. European Signal Processing Conference (EUSIPCO), 2025. [arXiv]
  4. J. Wang*, R. Shi*, B. Yen, et al. “Single-Microphone-Based Sound Source Localization for Mobile Robots in Reverberant Environments”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025. [arXiv] * equal contribution
  5. R. Shi, K. Li, Y. Wang, et al. “Unsupervised Single-Channel Speech Separation with Diffusion under Speaker-Embedding Guidance”. Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2026. [arXiv]
  6. R. Shi, C. Li, J. Li, et al. “Exploring Efficient Waveform Diffusion Models for Foley Sound Generation”. Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2026. [arXiv]
  7. R. Shi, Y. Wang, H. Song, et al. “Joint Residual Reweighting for Classifier Free Guidance in Flow-Matching Zero-Shot TTS”. Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2026. [arXiv]
  8. R. Shi, K. Itoyama, and K. Nakadai. “Bird Vocalization Embedding Extraction Using Self-Supervised Disentangled Representation Learning”. Vocal Interactivity in-and-between Humans, Animals and Robots (VIHAR), 2024. [arXiv]
  9. R. Shi, S. Yang, Y. Chen, et al. “CNN-Transformer for Visual Tactile Fusion Applied in Road Recognition of Autonomous Vehicles”. Pattern Recognition Letters, 2023. [DOI]
  10. R. Shi, S. Yang, J. Lu, et al. “Road Profile Reconstruction Based on Recurrent Neural Network Embedded with Attention Mechanism”. SAE Technical Paper, 2024. [DOI]
  11. R. Shi, S. Yang, Y. Chen, et al. “Road Recognition for Autonomous Vehicles Based on Intelligent Tire and SE-CNN”. Intelligent Systems and Pattern Recognition, 2022. [DOI]
  1. J. Wang, R. Shi, Y. Kang, et al. “Fast-SDE: Efficient Single-Microphone Sound Source Distance Estimation in Reverberant Environments”. arXiv preprint, 2026. [arXiv]
  2. J. Wang, R. Shi, J. Li, et al. “Manifold-Optimization-Based 3D Sound Source Mapping with Unknown Camera-Microphone Array Relative Pose”. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026. [DOI]
  3. N. Khan, B. Wu, R. Shi, et al. “From Sign Language Generation to Humanoid Execution: Vision-Language Guided Retargeting with Collision Mitigation”. arXiv preprint, 2026. [arXiv]
  4. Y. Kang, J. Wang, R. Shi, et al. “What Do Neural Networks Learn for TDOA Estimation? A Cross-Architecture Probing Study”. arXiv preprint, 2026. [arXiv]
  5. R. A. Nihal, B. Yen, R. Shi, et al. “Ecologically-Constrained Task Arithmetic for Multi-Taxa Bioacoustic Classifiers Without Shared Data”. arXiv preprint, 2026. [arXiv]
  6. R. A. Nihal, B. Yen, R. Shi, et al. “Weakly Supervised Multiple Instance Learning for Whale Call Detection and Localization in Long-Duration Passive Acoustic Monitoring”. arXiv preprint, 2025. [arXiv]
  7. R. Cao, Z. Zhang, R. Shi, et al. “Model-Constrained Deep Learning for Online Fault Diagnosis in Li-Ion Batteries over Stochastic Conditions”. Nature Communications, 2025. [DOI]
  8. J. Lu, Z. Peng, R. Shi, et al. “A Quantitative Blind Area Risks Assessment Method for Safe Driving Assistance”. Journal of Systems Architecture, 2024. [DOI]
  9. J. Lu, Y. Cao, R. Shi, et al. “An Efficient Driver Anomaly State Detection Approach Based on End-Cloud Integration and Unsupervised Learning”. IEEE International Conference on Intelligent Transportation Systems (ITSC), 2023. [DOI]
  10. J. Lu, S. Yang, R. Shi, et al. “Safety Co-Pilot: A System for Autonomous Vehicle to Make Decision Safer and Smarter”. IEEE International Conference on Intelligent Transportation Systems (ITSC), 2022. [DOI]
  11. S. Yang, Y. Chen, R. Shi, et al. “A Survey of Intelligent Tires for Tire-Road Interaction Recognition Toward Autonomous Vehicles”. IEEE Transactions on Intelligent Vehicles, 2022. [DOI]
  12. S. Yang, R. Wang, R. Shi, et al. “An Intelligent Tyre System for Road Condition Perception”. International Journal of Pavement Engineering, 2023. [DOI]