With the growth in digital representations of music, and of music stored in these representations, it is increasingly attractive to search collections of music. One mode of search is by similarity, but, for music, similarity search presents several difficulties: in particular, deciding what part of the music is likely to be perceived as the theme by a listener, and deciding whether two pieces of music with different sequences of notes represent the same theme. In this paper we propose a three-stage framework for matching pieces of music. We use the framework to compare a range of techniques for determining whether two pieces of music are similar, by experimentally testing their ability to retrieve different transcriptions of the same piece of music from a large collection of MIDI files. These experiments show that different comparison techniques differ widely in their effectiveness; and

We developed, and then evaluated, a music information retrieval (MIR) system based upon the intervals found within the melodies of a collection of 9354 folksongs. The songs were converted to an interval-only representation of monophonic melodies and then fragmented t into length-n subsections called n-grams. The length of these n-grams and the degree to which we precisely represent the intervals are variables analyzed in this paper. We constructed a collection of "musical word" databases using the text-based, SMART information retrieval system. A group of simulated queries, some of which contained simulated errors, was run against these databases. The results were evaluated using the normalized precision and normalized recall measures. Our concept of "musical words" shows great merit thus implying that useful MIR systems can be constructed simply and efficiently using pre-existing text-based information retrieval software. Second, this study is a formal and comprehensive evaluation of ...

This paper outlines the findings-to-date of a project to assist in the efforts being made to establish a TREC-like evaluation paradigm within the Music Information Retrieval (MIR) research community. The findings

User studies focusing upon real-life music information needs, uses and seeking behaviours are still very scarce in the music information retrieval (MIR) and music digital library (MDL) fields. We are conducting a multigroup survey in an attempt to acquire information that can help eradicate false assumptions in designing MIR systems. Our goal is to provide an empirical basis for MIR/MDL system development. In this paper, we present our preliminary findings and analyses based on the 427 user responses we have received to date. Two major themes have been uncovered thus far that could have a significant influence the future development of successful MIR/MDL systems. First, people display “public information-seeking ” behaviours by making use of collective knowledge and/or opinions of others about music such as reviews, ratings, recommendations, etc. in their music information-seeking. Second, respondents expressed needs for contextual metadata in addition to traditional bibliographic metadata.

Most research into music information retrieval thus far has only examined music from the western tradition. However, music of other origins often conforms to different tuning systems. Therefore there are problems both in representing this music as well as finding matches to queries from these diverse tuning systems. We discuss the issues associated with microtonal music retrieval and present some preliminary results from an experiment in applying scoring matrices to microtonal matching. 1.

Music Information Retrieval (MIR) is a multidisciplinary research endeavor that strives to develop innovative content-based searching schemes, novel interfaces, and evolving networked delivery mechanisms in an effort to make the world’s vast store of music accessible to all. Some teams are developing ‘‘Query-by-Singing’’ and ‘‘Query-by-Humming’’ systems that allow users to interact with their respective music search engines via queries that are sung or hummed into a microphone (e.g., Birmingham et al. 2001; Haus and Pollastri 2001). ‘‘Queryby-Note’’ systems are also being developed wherein searchers construct queries consisting of pitch and/or rhythm information (e.g., Pickens 2000; Doraisamy and Rüger 2002). Input methods for Queryby-Note systems include symbolic interfaces as well as both physical (MIDI) and virtual (Javabased) keyboards. Some teams are working on ‘‘Query-by-Example’’ systems that take prerecorded music in the form of CD or MP3 tracks as their query input (e.g., Haitsma and Kalker 2002; Harb and Chen 2003). The development of comprehensive music recommendation and distribution systems is a growing research area (e.g., Logan 2002; Pauws and Eggen 2002). The automatic generation of playlists for use in personal music systems, based on a wide variety of user-defined criteria, is the goal of this branch of MIR research. Other groups are investigating the creation of music analysis systems to assist those in the musicology and music theory communities (e.g., Barthélemy