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Fast query by humming system based on complex multiscale music entropy and CMMEB Kd tree

机译:基于复杂多尺度音乐熵和CMMEB Kd树的哼唱系统快速查询

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摘要

Query by Humming (QBH) Music Information Retrieval (MIR) system is one of the enlivened areas of research for matching hummed query to music excerpts existing within the music database. This paper proposes a fast QBH content based music retrieval technique based on the estimation of Complex Multiscale Music Entropy (CMME). The proposed concept exploits the statistical reliability through the CMME for approximation of music signals. In order to enhance the speed of the system, the CMME feature vectors of music database are indexed through Complex Multiscale Music Entropy Balanced (CMMEB) Kd tree leading to reduced search space and retrieval time. Eventually, CMME feature vectors are extracted from humming query for retrieval of the target song from music database. The experimental results effectually locate the humming queries and state the prominence of CMME and CMMEB Kd tree for retrieving the target song by humming.
机译:嗡嗡声查询(QBH)音乐信息检索(MIR)系统是使嗡嗡声查询与音乐数据库中存在的音乐摘录匹配的研究领域之一。提出了一种基于复杂多尺度音乐熵(CMME)估计的基于QBH内容的快速音乐检索技术。所提出的概念通过CMME利用统计可靠性来近似音乐信号。为了提高系统速度,通过复杂多尺度音乐熵平衡(CMMEB)Kd树对音乐数据库的CMME特征向量进行索引,从而减少了搜索空间和检索时间。最终,从哼唱查询中提取CMME特征向量,以从音乐数据库中检索目标歌曲。实验结果有效地定位了嗡嗡声查询,并指出了通过哼声检索目标歌曲的CMME和CMMEB Kd树的重要性。

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