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Visual-based spatial audio generation system for multi-speaker environments
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In multimedia applications such as films and video games, spatial audio techniques are widely employed to enhance user experiences by simulating 3D sound: transforming mono audio into binaural formats. However, this process is often complex and labor-intensive for sound designers, requiring precise synchronization of audio with the spatial positions of visual components. To address these challenges, we propose a visual-based spatial audio generation system - an automated system that integrates face detection YOLOv8 for object detection, monocular depth estimation, and spatial audio techniques. Notably, the system operates without requiring additional binaural dataset training. The proposed system is evaluated against existing Spatial Audio generation system using objective metrics. Experimental results demonstrate that our method significantly improves spatial consistency between audio and video, enhances speech quality, and performs robustly in multi-speaker scenarios. By streamlining the audio-visual alignment process, the proposed system enables sound engineers to achieve high-quality results efficiently, making it a valuable tool for professionals in multimedia production.
Forward citations
Cited by 2 Pith papers
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SonicGauss: Position-Aware Physical Sound Synthesis for 3D Gaussian Representations
A three-stage diffusion pipeline maps 3D Gaussian Splatting object representations to position-dependent impact sounds, trained first on text captions and then on real recordings.
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ASAudio: A Survey of Advanced Spatial Audio Research
A comprehensive survey that systematically categorizes spatial audio research by representation, task, dataset, and evaluation.
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