Iracema: a Python library for audio content analysis - Magalhaes, Tairone; Barros, Felippe; Loureiro, Maurício (Anais do Simpósio Brasileiro de Computação Musical (SBCM); 2019: Anais do XVII Simpósio Brasileiro de Computação Musical, 2019)
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 interface; and (4) give some brief examples of audio analysis using the system.