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Document Dependent Fusion in Multimodal Music Retrieval

机译:多模式音乐检索中基于文档的融合

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In this paper, we propose a novel multimodal fusion framework, document dependent fusion (DDF), which derives the optimal combination strategy for each individual document in the fusion process. For each document, we derive a document weight vector by estimating the descriptive abilities of its different modalities. The document weight vector also enables our framework to be easily integrated with existing multimodal fusion schemes, and achieve a better combination strategy for each document given a query. Experiments are conducted on a 17174-song music database to compare the retrieval accuracy of traditional query independent fusion and query dependent fusion approaches, and that obtained after integrating DDF with them. Experimental results indicate that DDF can significantly improve the retrieval performance of current fusion approaches.
机译:在本文中,我们提出了一种新颖的多模式融合框架,即文档依赖融合(DDF),该框架为融合过程中的每个单独文档导出了最佳组合策略。对于每个文档,我们通过估计其不同模式的描述能力来导出文档权重向量。文档权重向量还使我们的框架可以轻松地与现有的多峰融合方案集成,并在给定查询的情况下为每个文档实现更好的组合策略。在17174首歌曲音乐数据库上进行了实验,比较了传统查询独立融合和查询依赖融合方法以及将DDF与它们集成后获得的方法的检索精度。实验结果表明,DDF可以显着提高当前融合方法的检索性能。

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