Encoding Performance Data in MEI with the Automatic Music Performance Analysis and Comparison Toolkit (AMPACT)

Autor:	Devaney, Johanna, Beauchamp, Cecilia
Rok vydání:	2023
Předmět:	Computer Science - Sound Computer Science - Digital Libraries Electrical Engineering and Systems Science - Audio and Speech Processing
Zdroj:	Late-Breaking Demo Session of the 24th International Society for Music Information Retrieval Conference (2023)
Druh dokumentu:	Working Paper
Popis:	This paper presents a new method of encoding performance data in MEI using the recently added \texttt{} element. Performance data was extracted using the Automatic Music Performance Analysis and Comparison Toolkit (AMPACT) and encoded as a JSON object within an \texttt{} element linked to a specific musical note. A set of pop music vocals has was encoded to demonstrate both the range of descriptors that can be encoded in and how AMPACT can be used for extracting performance data in the absence of a fully specified musical score. Comment: 3 pages, 2 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.11363 Zobrazit plný text záznamu View this record from Arxiv