文献类型： 会议论文
第一作者： Yeyin Wang
作者： Yeyin Wang 1 ; Shenwei Wang 1 ;
作者机构： 1.China Academy of Aerospace Systems Science and Engineering, CAASSE, Beijing, China
关键词： Correlation;Accuracy;Lattices;Speech recognition;Big Data;Feature extraction;Complexity theory
会议名称： International Conference on Computer Engineering and Application
主办单位：
页码： 1071-1075
摘要： With the advent of the big data era, the amount of audio data is rapidly increasing. In order to effectively utilize this information, we urgently need an efficient method for retrieving speech information. This paper proposes a speech retrieval technology based on index fusion and pseudo correlation feedback to address the issue of insufficient accuracy in existing speech retrieval techniques. On the basis of multiple systems, inverted indexes are introduced for speech retrieval, and the keyword inverted index table is fused. This not only obtains the complementarity of detection systems, but also improves retrieval efficiency; Then calculate the similarity between the speech segments sorted for the first retrieval and the pseudo correlated and uncorrelated sets, and correspondingly reorder the return list for the first retrieval. By effectively utilizing the information hidden in the pseudo feedback document, optimize the sorting results and improve the retrieval accuracy.
分类号： tp3
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