The Interpersonal Entrainment in Music Performance Data Collection

Clayton, Martin - Tarsitani, Simone - Jankowsky, Richard - Jure, Luis - Leante, Laura - Polak, Rainer - Poole, Adrian - Rocamora, Martín - Alborno, Paolo - Camurri, Antonio - Eerola, Tuomas - Jacoby, Nori - Jakubowski, Kelly

Resumen:

The Interpersonal Entrainment in Music Performance Data Collection (IEMPDC) comprises six related corpora of music research materials: Cuban Son & Salsa (CSS), European String Quartet (ESQ), Malian Jembe (MJ), North Indian Raga (NIR), Tunisian Stambeli (TS), and Uruguayan Candombe (UC). The core data for each corpus comprises media files and computationally extracted event onset timing data. Annotation of metrical structure and code used in the preparation of the collection is also shared. The collection is unprecedented in size and level of detail and represents a significant new resource for empirical and computational research in music. In this article we introduce the main features of the data collection and the methods used in its preparation. Details of technical validation procedures and notes on data visualization are available as Appendices. We also contextualize the collection in relation to developments in Open Science and Open Data, discussing important distinctions between the two related concepts.


Detalles Bibliográficos
2021
Ethnomusicology
Music cognition
Computational musicology
Entrainment
Synchronization
Music performance
Open Science
FAIR principles
Inglés
Universidad de la República
COLIBRI
https://emusicology.org/issue/view/278
https://hdl.handle.net/20.500.12008/30458
Acceso abierto
Licencia Creative Commons Atribución - No Comercial (CC - By-NC 4.0)
Resumen:
Sumario:The Interpersonal Entrainment in Music Performance Data Collection (IEMPDC) comprises six related corpora of music research materials: Cuban Son & Salsa (CSS), European String Quartet (ESQ), Malian Jembe (MJ), North Indian Raga (NIR), Tunisian Stambeli (TS), and Uruguayan Candombe (UC). The core data for each corpus comprises media files and computationally extracted event onset timing data. Annotation of metrical structure and code used in the preparation of the collection is also shared. The collection is unprecedented in size and level of detail and represents a significant new resource for empirical and computational research in music. In this article we introduce the main features of the data collection and the methods used in its preparation. Details of technical validation procedures and notes on data visualization are available as Appendices. We also contextualize the collection in relation to developments in Open Science and Open Data, discussing important distinctions between the two related concepts.