MetrikaBox: An open framework for experimenting with audio classification

This paper presents MetrikaBox, a general-purpose, open-source, and extensible audio classification package designed to facilitate the development of Deep Learning (DL) models for a wide range of audio processing tasks. The software manages all necessary preprocessing steps to build classification models capable of distinguishing between user-defined classes using advanced Artificial Intelligence (AI) techniques. MetrikaBox is well suited for tasks such as musical genre classification, voice-versus-music discrimination, and other audio classification or segmentation applications. Users can either employ the package as provided or extend it by integrating their own datasets, classification models, data loading systems, augmentation techniques, and more. The package has been tested in both commercial and academic settings, where it has produced models for industrial audio processing and served as a platform for proof-of-concept applications. Comprehensive documentation and practical examples included in the repository support users in integrating the system into their audio analysis projects. MetrikaBox is openly available and provides a user interface for convenient testing.

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Publication Details

Journal
SoftwareX
Published
2025-08-28
DOI
https://doi.org/10.1016/j.softx.2025.102306
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00
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article

MetrikaBox: An open framework for experimenting with audio classification

Roberto Rodríguez-Echeverría, Fernando Sánchez-Figueroa, Jorge Perianez-Pascual, Juan D. Gutiérrez et al.
SoftwareX
Music and Audio Processing
article

MetrikaBox: An open framework for experimenting with audio classification

Roberto Rodríguez-Echeverría, Fernando Sánchez-Figueroa, Jorge Perianez-Pascual, Juan D. Gutiérrez, Emilio Delgado
article en

Abstract

This paper presents MetrikaBox, a general-purpose, open-source, and extensible audio classification package designed to facilitate the development of Deep Learning (DL) models for a wide range of audio processing tasks. The software manages all necessary preprocessing steps to build classification models capable of distinguishing between user-defined classes using advanced Artificial Intelligence (AI) techniques. MetrikaBox is well suited for tasks such as musical genre classification, voice-versus-music discrimination, and other audio classification or segmentation applications. Users can either employ the package as provided or extend it by integrating their own datasets, classification models, data loading systems, augmentation techniques, and more. The package has been tested in both commercial and academic settings, where it has produced models for industrial audio processing and served as a platform for proof-of-concept applications. Comprehensive documentation and practical examples included in the repository support users in integrating the system into their audio analysis projects. MetrikaBox is openly available and provides a user interface for convenient testing.

SoftwareXVol. 31
Universidade de Santiago de Compostela (ES), Universidad de Extremadura (ES)
Openalex Percentile: Top 72%
Music and Audio Processing
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MetrikaBox: An open framework for experimenting with audio classification — Roberto Rodríguez-Echeverría, Fernando Sánchez-Figueroa, et al. · SoftwareX (2025) | TGRS Research Map | TGRS