厦门大学学报（自然科学版）2013，Vol.52Issue(1)：32-37,6.
基于金字塔匹配核的音乐信息检索
Applying Pyramid Match Kernel to Music Information Retrieval
摘要
Abstract
One key step in the content-based music information retrieval (MIR) is feature extraction. The limitations of the traditional feature representation-single-feature-vector are obvious. First,it is difficult to select the segment/time window for extracting acoustic features; second,some important music information may be lost due to the selection of the specified segment. To address these two limitations,a novel feature representation method-multi-feature-vector in which multiple acoustic feature vectors over the music track can be obtained,was introduced to represent the music tracks. Motivated by the pyramid match kernel (PMK) which measures the similarity between two multi-feature-vectors with different sizes,PMK was used to extend the MIR techniques,so that the similarity between two music tracks which are represented by multi-feature-vectors can be accurately captured. Empirical results show that the incorporation of PMK into MIR tasks leads to the performance improvement.关键词
多特征向量/特征相似度/金字塔匹配核/音乐信息检索Key words
multi-feature vector/ feature similarity/ pyramid match kernel/ music information retrieval分类
信息技术与安全科学引用本文复制引用
洪文兴,李晶轩,郑思婷,李涛..基于金字塔匹配核的音乐信息检索[J].厦门大学学报（自然科学版）,2013,52(1):32-37,6.基金项目
福建省自然科学基金项目(2011J05157) （2011J05157）
