A Production-Oriented Framework for Evaluation of SFX Generation

2026-07-10

AI Summary

Existing audio generation evaluation methods struggle to simultaneously address the industrial sound design requirements of reference guidance, controllable variation, perceptual consistency, and workflow efficiency. This work proposes the first production-oriented evaluation framework for sound effect generation, structured around nine core production criteria and a two-stage protocol that enables systematic, goal-aligned comparison of heterogeneous generation and editing approaches. The framework integrates objective metrics—including Fréchet Audio Distance (FAD), ImageBind-based reference alignment, and diversity scores—with human listening experiments to holistically assess perceptual identity preservation and transient fidelity. Empirical results reveal complementary strengths across baseline methods, with AudioX achieving the best trade-off between reference alignment and output diversity while effectively supporting sound morphing tasks.

Abstract

Industrial sound design requires audio generation systems that not only produce realistic audio, but also preserve the perceptual identity of a reference, support controllable variation, and remain efficient for practical workflows. Existing evaluations are usually tied to text-to-audio (TTA), unconditional, or task-specific settings, limiting assessment for reference-guided sound effects (SFX) variation. To address this gap, we present a production-oriented evaluation framework for structured comparison of heterogeneous audio generation and editing methods. Our framework identifies nine production requirements and explicitly accounts for differences in model capabilities, enabling comparison under a common production objective. A two-stage protocol is introduced: (1) a reference-guided audio-to-audio (ATA) variation task, in which all methods are evaluated under the same ESC-50 SFX adaptation setup, and (2) capability-specific analyses of native operations such as SFX morphing, temporal and energy alignment, inpainting, and targeted editing. This framework combines objective metrics (including FAD, ImageBind-based reference alignment, and diversity across generated variants), together with a human study of perceptual identity preservation and transient diagnosis. Our study reveals complementary strengths and trade-offs across baselines for different production needs. Among the full-generation baselines evaluated under a shared ATA setting, AudioX provides the strongest overall trade-off between reference alignment and diversity while still supporting SFX morphing. Other baselines remain most suitable for specific editing operations. Our framework establishes a structured evaluation and decision protocol for reference-guided SFX variation and provides a practical basis for designing future unified industrial audio generation pipelines. Audio demos are on the accompanying web page.

Problem

• sound effects generation
• reference-guided audio
• production-oriented evaluation
• audio variation
• industrial audio design

Innovation

• reference-guided audio generation
• audio-to-audio variation
• production-oriented evaluation
• sound effects morphing
• perceptual identity preservation