26,360 research outputs found

    Music Similarity Estimation

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    Music is a complicated form of communication, where creators and culture communicate and expose their individuality. After music digitalization took place, recommendation systems and other online services have become indispensable in the field of Music Information Retrieval (MIR). To build these systems and recommend the right choice of song to the user, classification of songs is required. In this paper, we propose an approach for finding similarity between music based on mid-level attributes like pitch, midi value corresponding to pitch, interval, contour and duration and applying text based classification techniques. Our system predicts jazz, metal and ragtime for western music. The experiment to predict the genre of music is conducted based on 450 music files and maximum accuracy achieved is 95.8% across different n-grams. We have also analyzed the Indian classical Carnatic music and are classifying them based on its raga. Our system predicts Sankarabharam, Mohanam and Sindhubhairavi ragas. The experiment to predict the raga of the song is conducted based on 95 music files and the maximum accuracy achieved is 90.3% across different n-grams. Performance evaluation is done by using the accuracy score of scikit-learn

    The NEUMA Project: towards Cooperative On-line Music Score Libraries

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    Περιέχει το πλήρες κείμενοThe NEUMA project (http://neuma.irpmf-cnrs.fr) aims at designing and evaluating an open cooperative system for musician communities, enabling new search and analysis tools for symbolic musical content sharing and dissemination. The project is organized around the French CNRS laboratory of the Bibliothèque Nationale de France which provides sample collections, user requirements and expert validation. The paper presents the project goals, its achitecture and current state of development. We illustrate our approach with an on-line publication of monodic collections centered on XVIIe century French liturgic chants

    On the Complex Network Structure of Musical Pieces: Analysis of Some Use Cases from Different Music Genres

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    This paper focuses on the modeling of musical melodies as networks. Notes of a melody can be treated as nodes of a network. Connections are created whenever notes are played in sequence. We analyze some main tracks coming from different music genres, with melodies played using different musical instruments. We find out that the considered networks are, in general, scale free networks and exhibit the small world property. We measure the main metrics and assess whether these networks can be considered as formed by sub-communities. Outcomes confirm that peculiar features of the tracks can be extracted from this analysis methodology. This approach can have an impact in several multimedia applications such as music didactics, multimedia entertainment, and digital music generation.Comment: accepted to Multimedia Tools and Applications, Springe
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