Visual Mining in Music Collections
نویسندگان
چکیده
We describe the MusicMiner system for organizing large collections of music with databionic mining techniques. Visualization based on perceptually motivated audio features and Emergent Self-Organizing Maps enables the unsupervised discovery of timbrally consistent clusters that may or may not correspond to musical genres and artists. We demonstrate the visualization capabilities of the U-Map. An intuitive browsing of large music collections is offered based on the paradigm of topographic maps. The user can navigate the sound space and interact with the maps to play music or show the context of a song.
منابع مشابه
Visual mining in music collections with Emergent SOM
We describe different ways of organizing large collections of music with databionic mining techniques. The Emergent Self-Organizing Map is used to cluster and visualize similar artists and songs. The first method is the MusicMiner system that utilizes semantic descriptions learned from low level audio features for each song. The second method uses tags that have been assigned to songs and artis...
متن کاملMining music graphs through immanantal polynomials
Graphs represent an effective tool for modeling structural features of music in symbolic format. Here we show how it is possible to characterize a music graph by means of the second immanantal polynomial and how to embed the polynomial coefficients into a low dimensional vector space, biased on specific music collections, by means of Independent Component Analysis, thus allowing for music minin...
متن کاملVisualization in Comparative Music Research
Computational analysis of large musical corpora provides an approach that overcomes some of the limitations of manual analysis related to small sample sizes and subjectivity. The present paper aims to provide an overview of the computational approach to music research. It discusses the issues of music representation, musical feature extraction, digital music collections, and data mining techniq...
متن کاملComparative Analysis of Music Recordings from Western and Non-Western traditions by Automatic Tonal Feature Extraction
The automatic analysis of large musical corpora by means of computational models overcomes some limitations of manual analysis, and the unavailability of scores for most existing music makes necessary to work with audio recordings. Until now, research on this area has focused on music from the Western tradition. Nevertheless, we might ask if the available methods are suitable when analyzing mus...
متن کاملMelodic Pattern Extraction in Large Collections of Music Recordings Using Time Series Mining Techniques
We demonstrate a data-driven unsupervised approach for the discovery of melodic patterns in large collections of Indian art music recordings. The approach first works on single recordings and subsequently searches in the entire music collection. Melodic similarity is based on dynamic time warping. The task being computationally intensive, lower bounding and early abandoning techniques are appli...
متن کامل