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Visual-based spatial audio generation system for multi-speaker environments

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arxiv 2502.07538 v2 pith:5RHHK5P3 submitted 2025-02-11 cs.MM cs.SDeess.AS

classification cs.MMcs.SDeess.AS
keywords audiospatialsystemgenerationsoundbinauraldetectionmulti-speaker
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SonicGauss: Position-Aware Physical Sound Synthesis for 3D Gaussian Representations

    cs.SD 2025-07 conditional novelty 5.0 of 10

    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.

  2. ASAudio: A Survey of Advanced Spatial Audio Research

    eess.AS 2025-08 unverdicted novelty 3.0 of 10

    A comprehensive survey that systematically categorizes spatial audio research by representation, task, dataset, and evaluation.

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