publication . Article . Conference object . 2020

Iracema: a Python library for audio content analysis

Tairone Magalhães; Felippe Brandão Barros; Mauricio Alves Loureiro;
Open Access
  • Published: 23 Dec 2020 Journal: Revista de Informática Teórica e Aplicada, volume 27, pages 127-138 (issn: 0103-4308, eissn: 2175-2745, Copyright policy)
  • Publisher: Universidade Federal do Rio Grande do Sul
This paper introduces the alpha version of a Python library called Iracema, which aims to provide models for the extraction of meaningful information from recordings of monophonic pieces of music, for purposes of research in music performance. With this objective in mind, we propose an architecture that will provide to users an abstraction level that simplifies the manipulation of different kinds of time series, as well as the extraction of segments from them. In this paper we: (1) introduce some key concepts at the core of the proposed architecture; (2) list the current functionalities of the package; (3) give some examples of the application programming interf...
free text keywords: music; empirical study of music performance;, Music Expressiveness; Music Information Retrieval; Software Systems and Languages for Sound and Music, Audio analyzer, Computer science, Architecture, Abstraction layer, Audio content analysis, Programming language, computer.software_genre, computer, Music information retrieval, Python (programming language), computer.programming_language, Application programming interface
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