Sound design workflows frequently oscillate between time-consuming library searches and the complexity of procedural synthesis, with practitioners typically relying on disconnected tools to address each challenge separately. This paper introduces Quality Audio Prototyping (QuAP), a working prototype that unifies content-based audio retrieval and procedural sound generation within a single interface, reducing the procedural distance between a narrative concept and its sonic realisation. QuAP integrates a similarity-based retrieval engine with real-time procedural audio models, complemented by a rule-based assistant that provides perceptually informed parameter guidance, offering definitions and recommendations derived from empirical optimisation rather than requiring prior synthesis knowledge. Preliminary evaluation confirms the viability of this approach: subjective assessment demonstrated statistically significant quality improvements in five of six embedded synthesis models, and an encoder ablation study established the preferred retrieval architecture on a sound effect dataset. A user evaluation with 16 practitioners confirmed the tool's workflow utility, with all participants agreeing that the parameter assistant preserved creative agency while lowering the barrier to procedural interaction.

翻译：声音设计工作流程常常在耗时的音色库搜索与复杂的程序化合成之间摇摆，实践者通常依赖互不关联的工具分别应对这两类挑战。本文介绍高质量音频原型设计系统（QuAP）——一个将基于内容的音频检索与程序化声音生成统一于单一界面的工作原型，能够缩短从叙事概念到声音实现之间的程序化距离。QuAP集成了基于相似度的检索引擎与实时程序化音频模型，辅以基于规则的辅助系统，该系统提供基于感知的参数引导，通过经验优化而非先验合成知识给出定义与建议。初步评估证实了该方法的可行性：主观评价显示六个内置合成模型中有五个在统计分析上取得显著质量提升；编码器消融研究在音效数据集上确定了最优检索架构。针对16位实践者的用户评估证实了该工具对工作流程的实用价值，所有参与者均认同参数辅助系统在降低程序化交互门槛的同时保持了创作自主性。