An architecture for effective music information retrieval

2005

This survey paper provides an overview of content-based music information retrieval systems, both for audio and for symbolic music notation. Matching algorithms and indexing methods are briefly presented. The need for a TREC-like comparison of matching algorithms such as MIREX at ISMIR becomes clear from the high number of quite different methods which so far only have been used on different data collections. We placed the systems on a map showing the tasks and users for which they are suitable, and we find that existing content-based retrieval systems fail to cover a gap between the very general and the very specific retrieval tasks.

Journal of the American Society for Information Science and Technology, 2004

As the dimension and number of digital music archives grow, the problem of storing and accessing multimedia data is no longer confined to the database area. Specific approaches for music information retrieval are necessary to establish a connection between textual and content-based metadata. This article addresses such issues with the intent of surveying our perspective on music information retrieval. In particular, we stress the use of symbolic information as a central element in a complex musical environment. Musical themes, harmonies, and styles are automatically extracted from electronic music scores and employed as access keys to data. The database schema is extended to handle audio recordings. A score/audio matching module provides a temporal relationship between a music performance and the score played. Besides standard free-text search capabilities, three levels of retrieval strategies are employed. Moreover, the introduction of a hierarchy of input modalities assures meeting the needs and matching the expertise of a wide group of users. Singing, playing, and notating melodic excerpts is combined with more advanced musicological queries, such as querying by a sequence of chords. Finally, we present some experimental results and our future research directions.

Transactions on Machine Learning and Artificial Intelligence, 2018

Digitization of music and advancements in information technology for sharing information on World Wide Web paved way for its availability in enormous quantities anywhere any time. Rather than retrieving annotated music in response to query given in terms of Metadata such as name of the composer/singer, genre etc modern researchers are challenged towards content based music information retrieval systems (CBMIR). CBMIR systems differ while representing the main melody either as a note sequence or as an analog acoustic signal; the note sequence representation is explored in this research work. Based on the observation that repeating patterns of the note sequences representing the main melody capture the essence of the music object, this research work developed a framework to investigate the feasibility and effectiveness of pattern based melody matching approach to music information retrieval. Experimentation is conducted on a real world dataset of musical objects belonging to South Indian classical music and the performance of the framework is estimated in terms of Mean Reciprocal Ranking.

National Conference on Communications, Bombay, …, 2002

This paper describes some early attempts at developing a music indexing and retrieval system based on melody, or tune, of songs. In the envisaged system, the "query", a song fragment whistled or sung by the user into a microphone, is used to search a database of soundtracks to find the entry that is best matched to it in tune. The challenging issues that this project raises are described. Signal processing tools suitable for melody detection are presented, and finally some experimentally obtained results are discussed.

International Symposium/Conference on Music Information Retrieval, 2000

The origins of music information retrieval (MIR) are in manual collections of incipits, short melodic fragments obtained from the beginning of pieces of music. The collections were manually compiled and usually covered a narrow field of music. Recently, computerized content- based MIR systems have appeared. They apply standard methods from general string matching. The applied techniques are based on the

Signals and Communication Technology, 2017

ACM Multimedia Conference, 2000

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 that, by instantiating the framework with appropriate music manipulation and comparison techniques, pieces of music that match a query can be identified in a large collection.

Journal of Intelligent Information Systems

Increasing availability of music data via Internet evokes demand for efficient search through music files. Users' interests include melody tracking, harmonic structure analysis, timbre identification, and so on. We visualize, in an illustrative example, why content based search is needed for music data and what difficulties must be overcame to build an intelligent music information retrieval system.

1997

This paper describes a system designed to retrieve melodies from a database on the basis of a few notes sung into a microphone. The system first accepts acoustic input from the user, transcribes it into common music notation, then searches a database of 9400 folk tunes for those containing the sung pattern, or patterns similar to the sung pattern; retrieval is ranked according to the closeness of the match. The paper presents an analysis of the performance of the system using different search criteria involving melodic contour, musical intervals and rhythm; tests were carried out using both exact and approximate string matching. Approximate matching used a dynamic programming algorithm designed for comparing musical sequences. Current work focuses on developing a faster algorithm.

The digital revolution has brought about a massive increase in the availability and distribution of music-related documents of various modalities comprising textual, audio, as well as visual material. Therefore, the development of techniques and tools for organizing, structuring, retrieving, navigating, and presenting music-related data has become a major strand of research—the field is often referred to as Music Information Retrieval (MIR). Major challenges arise because of the richness and diversity of music in form and content leading to novel and exciting research problems. In this article, we give an overview of new developments in the MIR field with a focus on content-based music analysis tasks including audio retrieval, music synchronization, structure analysis, and performance analysis.