Scaling and compressing melodies using geometric similarity measures
作者：
Highlights：
• We propose efficient algorithms for two geometric problems that arise in music information retrieval; linear scaling and data compression.
• Linear scaling is used for tempo variation and melody matching, while an important application of data compression is clustering and classification.
• We use geometric matching techniques to measure the similarity between two melodies.
• Our algorithms take advantage of the properties of an optimal solution and are based on line sweeping and dynamic programming techniques.
摘要
•We propose efficient algorithms for two geometric problems that arise in music information retrieval; linear scaling and data compression.•Linear scaling is used for tempo variation and melody matching, while an important application of data compression is clustering and classification.•We use geometric matching techniques to measure the similarity between two melodies.•Our algorithms take advantage of the properties of an optimal solution and are based on line sweeping and dynamic programming techniques.
论文关键词：Melodic similarity,Geometric,Matching,Algorithm,Scaling,Compressing
论文评审过程：Received 17 May 2021, Revised 25 March 2022, Accepted 27 March 2022, Available online 8 April 2022, Version of Record 8 April 2022.
论文官网地址：https://doi.org/10.1016/j.amc.2022.127130
