Computational Modeling in Python for the Analysis of Choros: Hybrid Techniques for Pattern Extraction in Brazilian Popular Music - Yasuda, Rafael Mitsuru (Anais do Simpósio Brasileiro de Computação Musical; 2025: Anais do XIX Simpósio Brasileiro de Computação Musical, 2025)
This article proposes a hybrid methodology for the computational analysis of the works of Aníbal Augusto Sardinha (Garoto), recognized as one of the most significant figures of instrumental Brazilian choro. The approach integrates symbolic and acoustic analysis procedures utilizing the Python libraries music21 and librosa, enabling automated extraction of structural and expressive parameters from digitized scores and historical recordings. The symbolic corpus is based on the Songbook Choros de Garoto (SESC/IMS), encompassing approximately fifty pieces converted into the MusicXML format. Whenever available, original recordings by Garoto are employed for acoustic analysis, allowing investigation of interpretative aspects such as dynamics, timbre, and tempo. The methodology includes the extraction of tonalities, structural forms, harmonic progressions, melodic n-grams, Mel-frequency cepstral coefficients (MFCCs), chromagrams, and energy curves. Symbolic and acoustic data are integrated into a tabular structure using the pandas library, facilitating exploratory analysis through techniques such as Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE). This study represents the initial stage of ongoing doctoral research and aims to contribute to the systematization of computational tools for stylistic studies of Brazilian popular music.