A tempo-insensitive distance measure for cover song identification based on chroma features
We present a distance measure between audio files designed to identify cover songs, which are new renditions of previously recorded songs. For each song we compute the chromagram, remove phase information and apply exponentially distributed bands in order to obtain a feature matrix that compactly describes a song and is insensitive to changes in instrumentation, tempo and time shifts. As distance between two songs, we use the Frobenius norm of the difference between their feature matrices normalized to unit norm. When computing the distance, we take possible transpositions into account. In a test collection of 80 songs with two versions of each, 38% of the covers were identified. The system was also evaluated on an independent, international evaluation where it despite having much lower complexity performed on par with the winner of last year.