With Islands of Music we present a system which facilitates exploration of music libraries without requiring manual genre classification. Given pieces of music in raw audio format we estimate their perceived sound similarities based on psychoacoustic models. Subsequently, the pieces are organized on a 2-dimensional map so that similar pieces are located close to each other. A visualization using a metaphor of geographic maps provides an intuitive interface where islands resemble genres or styles of music. We demonstrate the approach using a collection of 359 pieces of music.

With the advent of large musical archives the need to provide an organization of these archives becomes eminent. While artist-based organizations or title indexes may help in locating a specific piece of music, a more intuitive, genre-based organization is required to allow users to browse an archive and explore its contents. Yet, currently these organizations following musical styles have to be designed manually.

. We are experiencing a tremendous increase in the amount of music being made available in digital form. With the creation of large multimedia collections, however, we need to devise ways to make those collections accessible to the users. While music repositories exist today, they mostly limit access to their content to query-based retrieval of their items based on textual meta-information, with some advanced systems supporting acoustic queries. What we would like to have additionally, is a way to facilitate exploration of musical libraries. We thus need to automatically organize music according to its sound characteristics in such a way that we nd similar pieces of music grouped together, allowing us to nd a classical section, or a hard-rock section etc. in a music repository. In this paper we present an approach to obtain such an organization of music data based on an extension to our SOMLib digital library system for text documents. Particularly, we employ the Self-Organizing Map to create a map of a musical archive, where pieces of music with similar sound characteristics are organized next to each other on the two-dimensional map display. Locating a piece of music on the map then leaves you with related music next to it, allowing intuitive exploration of a music archive. Keywords: Multimedia, Music Library, Self-Organizing Map (SOM), Exploration of Information Spaces, User Interface, MP3 1

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Journal of New Music Research 0929-8215/03/3202-193$16.00 2003, Vol. 32, No. 2, pp. 193–210 © Swets & Zeitlinger

The field of music provides an interesting context for the development of digital library systems due to the variety of information formats used by music students and scholars. The VARIATIONS digital library project at Indiana University currently delivers online access to sound recordings from the collections of IU's William and Gayle Cook Music Library and is developing access to musical score images and other formats. This paper covers the motivations for the creation of VARIATIONS, an overview of its operation and implementation, user reactions to the system, and future plans for development. Keywords Digital libraries, music libraries, digital audio. 1. INTRODUCTION The VARIATIONS project at Indiana University Bloomington currently provides online access within the William and Gayle Cook Music Library to over 5,000 sound recordings from the library's collections. Unlike many digital library projects whose primary goal is to provide broader access to unique and/or archival coll...

We present an efficient prototype for music information retrieval. The prototype uses bitparallel algorithms for locating transposition invariant matches of monophonic query melodies within monophonic or polyphonic music stored in a database. When dealing with monophonic music, we employ a fast approximate bit-parallel algorithm with special edit distance metrics.

People identify powerfully with music: someone might say thats my song! but they are unlikely to say thats my book! or thats my picture! A digital library of popular music therefore has the potential to be a compelling application of information retrieval technology. Such a library requires a retrieval method that is appropriate for a non-technical audience. Experiments on query by humming, which attempt to retrieve a tune based on sampled recording of a user singing an excerpt, have heretofore concentrated on relatively small, well-curated collections. Scaling up introduces three problems: availability of source material, an increase in false positive hits, and slower retrieval. We describe our experiments with MIDI files, propose a new, more accurate distance metric between queries and songs, and discuss possibilities for efficient indexing. 1.# INTRODUCTION Digital libraries until now could hardly be described as popular: they tend to be based on esoteric, scholarly sources close ...

With the increasing amount of music available electronically, methods for organizing these collections to allow intuitive browsing and orientation gain importance. Due to the large amounts of data involved, conventional approaches to organize music by genre or musical style are only of limited applicability, commonly relying on textual descriptions and manual classification. This makes it a particularly challenging application arena for neural networks capable of handling very high-dimensional input spaces and the noisy patterns associated with musical data. In this paper we present a system based on the Self-Organizing Map which automatically organizes a collection of music files according to their musical genre and sound characteristics. Frequency spectra are used to extract feature vectors describing sound and melody characteristics. A two-stage clustering procedure first groups music segments according to their similarity, followed by a clustering of compositions according to the segment similarities. As a result, pieces of music with similar sound characteristics are found in neighboring regions of the resulting map, thus offering a very intuitive interface to unknown music collections.

There has been substantial research on technical aspects of musical digital libraries, but comparatively little on usability aspects. We have evaluated four web-accessible music libraries, focusing particularly on features that are particular to music libraries, such as music retrieval mechanisms. Although the original focus of the work was on how modalities are combined within the interactions with such libraries, that was not where the main difficulties were found. Libraries were generally well designed for use of different modalities. The main challenges identified relate to the details of melody matching and to simplifying the choices of file format. These issues are discussed in detail. 1.

This paper reports on a system for musical information retrieval environments called SMILE. SMILE implements a methodology designed to cope with content-based musical retrieval. The innovation provided by the methodology is due to the synergic combination of sound information retrieval techniques and computer-based melodic surface extraction algorithms. The innovative corollary is that the latter extracts content-descriptive musical phrases from both documents and queries by thus permitting a clear separation between information being searched and indexes describing the semantic content. The information retrieval techniques are employed to index, retrieve, and rank by score the musical documents judged relevant to the final users' information need. Two types of retrieval functions are provided -- a querying function based on a virtual keyboard played by the user, and a browsing function to navigate an automatically constructed hyper-music which is made of documents and phrase...