Holographic voice-interactive system with Taylor Rayleigh-Sommerfeld based point cloud gridding

In recent years, intelligent voice interaction technology and holographic display technology have garnered significant attention. We propose a holographic voice-interactive system. The holographic voice interaction system can provide users with a virtual assistant proficient in accurately handling user voice queries, facilitating smoother interactions. Additionally, users can interact with virtual objects via holographic projection, enhancing realism and engagement. In this research, we introduce the U-blocks and U-net based reverse attention residual algorithm to generate more effective and accurate point cloud datasets during the acquisition phase. Furthermore, we integrate the ChatGLM pre-trained language model as the core module for voice interaction in the holographic display system, covering aspects such as text interaction and output control. Additionally, we propose a Taylor Rayleigh-Sommerfeld point cloud gridding method aimed at improving the computational speed of hologram generation. We validate the feasibility of our proposed methods through numerical simulations and optical experiments.