Multimodal similarity between musical streams for cover version detection

Abstract

Expressing the similarity between musical streams is a challenging task as it involves the understanding of many factors which are most often blended into one information channel: the audio stream. Consequently, separating the musical audio stream into its main melody and its accompaniment may prove as being useful to root the similarity computation on a more robust and expressive representation. In this paper, we show that considering the mixture, an estimation of its main melody and its accompaniment as modalities allows us to propose new ways of defining the similarity between musical streams. In the context of the detection of cover version, we show that highest performance is achieved by jointly considering the mixture and the estimated accompaniment. As demonstrated by the experiments carried out using two different evaluation databases, this scheme allows the scoring system to focus more on the chord progression by considering the accompaniment while being robust to the potential separation errors by also considering the mixture.