计算机工程与应用2012，Vol.48Issue(29)：133-136,219,5.DOI:10.3778/j.issn.1002-8331.2012.29.027
基于稀疏表示分类器的和弦识别研究
Research of chord recognition based on sparse representation classification
摘要
Abstract
Chord recognition as the basis of automatic musical information label plays an important role in analyzing the music structure, transcribing the note and identifying the melody. According to the related music theory this paper proposes a new chord recognition approach based on the beat synchronization and the SRC (Sparse Representation-based Classification). Different from the traditional frame-based methods, the proposed method considers the beat as the fundamental time slot for chord variation. It applies CQT(Constant-Q Transform) to perform the time-frequency analysis to the music signal to abstract the PCP(Pitch Class Profile) feature, and recognizes the chords by SRC. The experimental results show that the new method is better than the template-based method.关键词
和弦识别/节拍跟踪/音级轮廓(PCP)/稀疏表示分类器Key words
chord recognition/ beat tracking/ Pitch Class Profile (PCP)/ Sparse Representation-based Classification (SRC)分类
信息技术与安全科学引用本文复制引用
董丽梦,李锵,关欣..基于稀疏表示分类器的和弦识别研究[J].计算机工程与应用,2012,48(29):133-136,219,5.基金项目
国家自然科学基金(No.61101225,No.60802049) （No.61101225,No.60802049）
天津大学自主创新基金(No.60302015). （No.60302015）
