17,200 research outputs found

    Towards the disintermediation of creative music search: Analysing queries to determine important facets

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    Purpose: Creative professionals search for music to accompany moving images in films, advertising, television. Some larger music rights holders (record companies and music publishers) organise their catalogues to allow online searching. These digital libraries are organised by various subjective musical facets as well as by artist and title metadata. The purpose of this paper is to present an analysis of written queries relating to creative music search, contextualised and discussed within the findings of text analyses of a larger research project whose aim is to investigate meaning making in this search process. Method: A facet analysis of a collection of written music queries is discussed in relation to the organisation of the music in a selection of bespoke search engines. Results: Subjective facets, in particular Mood, are found to be highly important in query formation. Unusually, detailed Music Structural aspects are also key. Conclusions: These findings are discussed in relation to disintermediation of this process. It is suggested that there are barriers to this, both in terms of classification and also commercial / legal factors

    Organizing digital music for use: an examination of personal music collections

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    Current research on music information retrieval and music digital libraries focuses on providing access to huge, public music collections. In this paper we consider a different, but related, problem: supporting an individual in maintaining and using a personal music collection. We analyze organization and access techniques used to manage personal music collections (primarily CDs and MP3 files), and from these behaviors, to suggest user behaviors that should be supported in a personal music digital library (that is, a digital library of an individual's personal music collection)

    Visual collaging of music in a digital library

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    This article explores the role visual browsing can play within a digital music library. The context to the work is provided through a review of related techniques drawn from the fields of digital libraries and human computer interaction. Implemented within the open source digital library toolkit Greenstone, a prototype system is described that combines images located through textual metadata with a visualisation technique known as collaging to provide a leisurely, undirected interaction with a music collection. Emphasis in the article is given to the augmentations of the basic technique to work in the musical domain

    Challenges in cross-cultural/multilingual music information seeking

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    Understanding and meeting the needs of a broad range of music users across different cultures and languages are central in designing a global music digital library. This exploratory study examines cross-cultural/multilingual music information seeking behaviors and reveals some important characteristics of these behaviors by analyzing 107 authentic music information queries from a Korean knowledge search portal Naver (knowledge) iN and 150 queries from Google Answers website. We conclude that new sets of access points must be developed to accommodate music queries that cross cultural or language boundaries

    Multimodal music information processing and retrieval: survey and future challenges

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    Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music. Such modalities include audio recordings, symbolic music scores, mid-level representations, motion, and gestural data, video recordings, editorial or cultural tags, lyrics and album cover arts. This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval and highlights how multimodal algorithms can help Music Computing applications. First, we categorize the related literature based on the application they address. Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus in the next years

    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
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