In the study, we present a higher effective algorithm, called revised gene expression programming (RGEP), to construct the model for music emotion recognition. Our main contributions are as follows: firstly, we describe the basic mechanisms of music emotion recognition and introduce gene expression programming (GEP) to deal with the model construction for music emotion recognition. Secondly, we...

In the context of musical analysis, we propose an algorithm that automatically induces patterns from polyphonies. We define patterns as “perceptible repetitions in a musical piece”. The algorithm that measures the repetitions relies on some general perceptive notions: it is non-linear, non-symetric and non-transitive. The model can analyse any music of any genre that contains a beat. The analys...

In this paper we report on a public display where the audience is able to interact not only with visuals, but also with music. The interaction with music in a public setting involves some challenges, such as that passers-by as ‘novice users’ engage only momentarily with public displays and often don’t have any musical knowledge. We present a system that allows users to create harmonic melodies ...

Music recommendation has gained substantial attention in recent times. As one of the most important context features, user emotion has great potential to improve recommendations, but this has not yet been sufficiently explored due to the difficulty of emotion acquisition and incorporation. This paper proposes a graph-based emotion-aware music recommendation approach (GEMRec) by simultaneously t...

The study of music is highly interdisciplinary, and thus requires the combination of datasets from multiple musical domains, such as catalog metadata (authors, song titles, dates), industrial records (labels, producers, sales), and music notation (scores). While today an abundance of music metadata exists on the Linked Open Data cloud, linked datasets containing interoperable symbolic descripti...

The number of copyright registrations for music documents is increasing each year. Computer-based systems may help to detect near-duplicate music documents and plagiarisms. The main part of the existing systems for the comparison of symbolic music are based on string matching algorithms and represent music as sequences of notes. Nevertheless, adaptation to the musical context raises specific pr...

Audio source separation is a useful preprocessing step for remixing or transcription of music. It can be shown, that the separation quality increases, if the separation algorithm gets additional side information, e.g. the score of the current mixture [5]. In many cases the score of a musical piece is not available and has to be extracted by a professional musician or an automatic music transcri...

In this paper, we formulate diffuse optical tomography (DOT) problems as a source localization problem and propose a MUltiple SIgnal Classification (MUSIC) algorithm for functional brain imaging application. By providing MUSIC spectra for major chromophores such as oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR), we are able to investigate the spatial distribution of brain activities. Moreover,...

The contribution of this paper is threefold: First, we propose modifications to Fluctuation Patterns [14]. The resulting descriptors are evaluated in the task of rhythm similarity computation on the “Ballroom Dancers” collection. Second, we show that by combining these rhythmic descriptors with a timbral component, results for rhythm similarity computation are improved beyond the level obtained...