Facilitating Music Information Research with Shared Open Vocabularies

Facilitating Music Information Research with Shared Open Vocabularies
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通过共享开放词汇促进音乐信息研究

DOI:
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发表时间:
2013
期刊:
Extended Semantic Web Conference
影响因子:
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通讯作者:
M. Sandler
M. Sandler
中科院分区:
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文献类型:
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作者:
Alo Allik;György Fazekas;S. Dixon;M. Sandler

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在音乐信息检索领域,目前还没有关于音频特征的共同共享表示的协议。音频特征本体已经被开发为模块本体的协调库的一部分,以解决音乐相关数据源之间的互操作性问题。我们展示了一个软件框架,它结合了这个本体和相关的语义Web技术与数据提取和分析软件,以提高音频特征提取工作流程。
There is currently no agreement on common shared representations of audio features in the field of music information retrieval. The Audio Feature Ontology has been developed as part of a harmonised library of modular ontologies to solve the problem of interoperability between music related data sources. We demonstrate a software framework which combines this ontology and related Semantic Web technologies with data extraction and analysis software, in order to enhance audio feature extraction workflows.
DOI: 10.1080/09298215.2010.536555
发表时间: 2010-12
影响因子: 1.1
作者:
György Fazekas;Yves Raimond;Kurt Jacobson;M. Sandler
通讯作者: György Fazekas;Yves Raimond;Kurt Jacobson;M. Sandler