让AI音频模型无缝接入DAW，创作者可直接在软件内使用前沿AI处理声音。
HARP 2.0: Expanding Hosted, Asynchronous, Remote Processing for Deep Learning in the DAW
- 通过远程异步处理，将AI模型嵌入DAW插件界面
- 支持MIDI与音视频标注模型，拓展创作可能性
- 提供简洁API和稳定界面，降低开发者与艺术家使用门槛
HARP 2.0 通过托管式、异步远程处理，将深度学习模型引入数字音频工作站（DAW）软件，使用户可通过兼容Gradio的端点，将插件中的音频流经任意模型进行任意变换。处理后的音频与模型控制界面直接渲染在插件内，用户无需离开DAW即可探索多种前沿AI模型。2.0版本新增对MIDI模型与音频/MIDI标注模型的支持，提供简化的pyharp Python API供模型开发者使用，并实现多项界面优化与稳定性提升。本工作旨在弥合模型开发者与创作者之间的鸿沟，通过无缝集成提升深度学习模型在音频创作流程中的可访问性。
原文摘要 · Abstract (English)
HARP 2.0 brings deep learning models to digital audio workstation (DAW) software through hosted, asynchronous, remote processing, allowing users to route audio from a plug-in interface through any compatible Gradio endpoint to perform arbitrary transformations. HARP renders endpoint-defined controls and processed audio in-plugin, meaning users can explore a variety of cutting-edge deep learning models without ever leaving the DAW. In the 2.0 release we introduce support for MIDI-based models and audio/MIDI labeling models, provide a streamlined pyharp Python API for model developers, and implement numerous interface and stability improvements. Through this work, we hope to bridge the gap between model developers and creatives, improving access to deep learning models by seamlessly integrating them into DAW workflows.
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