Xiangyuan Yang — accepted AI-conference papers

2026

Diff-V2M: A Hierarchical Conditional Diffusion Model with Explicit Rhythmic Modeling for Video-to-Music Generation

Shulei Ji, Zihao Wang, Jiaxing Yu, Xiangyuan Yang, Shuyu Li, Songruoyao Wu +1

AAAI 2026technical

Video-to-music (V2M) generation aims to create music that aligns with visual content. However, two main challenges persist in existing methods: (1) the lack of explicit rhythm modeling hinders audiovisual temporal alignments; (2) effectively integrating various visual features to condition music gen

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2023

A Multi-Stage Triple-Path Method For Speech Separation in Noisy and Reverberant Environments

Zhaoxi Mu, Xinyu Yang, Xiangyuan Yang, Wenjing Zhu

ICASSP 2023accepted

In noisy and reverberant environments, the performance of deep learning-based speech separation methods drops dramatically because previous methods are not designed and optimized for such situations. To address this issue, we propose a multi-stage end-to-end learning method that decouples the diffic…

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