An Approach for Perceptual Similarity Detection between Audios Independent of Genre via Metadata Extraction and Correlation

Abstract

This study presents an approach for perceptual similarity detection between audios independent of genre. The study is formed of three phases; signal pre-processing as the first phase, metadata extraction via various perceptually compatible features as the second phase, and correlation methodology for similarity identification as the third phase. The performance and relative importance of the selected features for perceptual similarity analysis are presented, as testing results. Moreover, relative importance of preprocessing is introduced. Using the proposed methodology, perceptual similarity detection between genre independent audios is achieved with a 96.85% performance. Contribution highly lies on the independency of genre.