Music information retrieval

From Wikipedia, the free encyclopedia

This article or section needs copy editing for grammar, style, cohesion, tone or spelling.
You can assist by editing it now. A how-to guide is available. (May 2008)

Music information retrieval or MIR is the interdisciplinary science of retrieving information from music.

This includes:

Computational methods for classification, clustering, and modelling — Musical feature extraction for mono- and polyphonic music, similarity and pattern matching, retrieval
Formal methods and databases — Applications of automated music identification and recognition, such as score following, automatic accompaniment, Routing and filtering for music and music queries, Query languages, Standards and other metadata or protocols for music information handling and retrieval, Multi-agent systems, distributed search)
Software for music information retrieval — Semantic Web and musical digital objects, Intelligent agents, Collaborative software, Web-based search and semantic retrieval, query by humming, acoustic fingerprinting
Human-computer interaction and interfaces — Multi-modal interfaces, User interfaces and usability, Mobile applications, User behaviour
Music perception, cognition, affect, and emotions — Music similarity metrics, Syntactical parameters, Semantic parameters, Musical forms, structures, styles and genres, Music annotation methodologies
Music analysis and knowledge representation — Automatic summarization, citing, excerpting, downgrading, transformation, Formal models of music, digital scores and representations, Music indexing and metadata
Music archives, libraries, and digital collections — Music digital libraries, Public access to musical archives, Benchmarks and research databases
Intellectual property rights and music — National and international intellectual property right issues, Digital rights management, Identification and traceability
Sociology and Economy of music — Music industry and use of MIR in the production, distribution, consumption chain, User profiling, Validation, User needs and expectations, evaluation of music IR systems, building test collections, experimental design and metrics