Natural language processing for music knowledge discovery. Issue 4 (8th August 2018)

• Record Type: Journal Article
• Authors: Oramas, Sergio; Espinosa-Anke, Luis; Gómez, Francisco; Serra, Xavier
• Is Part Of: Journal of new music research. Volume 47:Issue 4(2018)
• Page Start: 365
• Page End: 382
• Publication Date: 2018-08-08
• Subjects: Musicology -- natural language processing -- information extraction -- entity linking -- sentiment analysis; Music -- Periodicals; Musicology -- Periodicals; 780.72
• DOI: 10.1080/09298215.2018.1488878
• Languages: English
• ISSNs: 0929-8215

Abstract

ABSTRACT: Today, a massive amount of musical knowledge is stored in written form, with testimonies dated as far back as several centuries ago. In this work, we present different Natural Language Processing (NLP) approaches to harness the potential of these text collections for automatic music knowledge discovery, covering different phases in a prototypical NLP pipeline, namely corpus compilation, text-mining, information extraction, knowledge graph generation, and sentiment analysis. Each of these approaches is presented alongside different use cases (i.e. flamenco, Renaissance and popular music) where large collections of documents are processed, and conclusions stemming from data-driven analyses are presented and discussed.