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A Knowledge Representation Framework for Context-Dependent Audio Processing

机译:用于上下文相关音频处理的知识表示框架

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This paper presents a general framework for using appropriately structured information about audio recordings in music processing, and shows how this framework can be utilised in multitrack music production tools. The information, often referred to as metadata, is commonly represented in a highly domain and application specific format. This prevents interoperability and its ubiquitous use across applications. In this paper, we address this issue. The basis for the formalism we use is provided by Semantic Web ontologies rooted in formal logic. A set of ontologies are used to describe structured representation of information such as tempo, the name of instruments or onset times extracted from audio. This information is linked to audio tracks in music production environments as well as processing blocks such as audio effects. We also present specific case studies, for example, the use of audio effects capable of processing and predicting metadata associated with the processed signals. We show how this increases the accuracy of description, and reduces the computational cost, by omitting repeated application of feature extraction algorithms.
机译:本文介绍了一个通用框架,用于在音乐处理中使用有关录音的适当结构化信息,并说明了如何在多轨音乐制作工具中利用此框架。该信息通常称为元数据,通常以高度域化和特定于应用程序的格式表示。这可防止互操作性及其在应用程序中的普遍使用。在本文中,我们解决了这个问题。我们使用的形式主义的基础是源于形式逻辑的语义Web本体。一组本体用于描述信息的结构化表示,例如速度,乐器名称或从音频中提取的开始时间。此信息链接到音乐制作环境中的音轨以及诸如音频效果之类的处理块。我们还介绍了具体的案例研究,例如,使用能够处理和预测与已处理信号关联的元数据的音频效果。我们展示了如何通过省略特征提取算法的重复应用来提高描述的准确性,并降低计算成本。

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