Music Information Retrieval
| Autor: | Burgoyne, J.A., Fujinaga, I., Downie, J.S., Schreibman, S., Siemens, R., Unsworth, J. |
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| Přispěvatelé: | Language and Computation (ILLC, FNWI/FGw), ILLC (FGw), Faculteit der Geesteswetenschappen, Brain and Cognition |
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | A new companion to digital humanities, 213-228 STARTPAGE=213;ENDPAGE=228;TITLE=A new companion to digital humanities |
| DOI: | 10.1002/9781118680605.ch15 |
| Popis: | 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.” MIR was born from computational musicology in the 1960s and has since grown to have links with music cognition and audio engineering, a dedicated annual conference (ISMIR) and an annual evaluation campaign (MIREX). MIR combines machine learning with expert human knowledge to use digital music data – images of music scores, “symbolic” data such as MIDI files, audio, and metadata about musical items – for information retrieval, classification and estimation, or sequence labeling. This chapter gives a brief history of MIR, introduces classical MIR tasks from optical music recognition to music recommendation systems, and outlines some of the key questions and directions for future developments in MIR. |
| Databáze: | OpenAIRE |
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