Instrumental Sensibility of Vocal Detector Based on Spectral Features

  • Shayenne Moura University of São Paulo
  • Marcelo Queiroz University of São Paulo

Resumo


Detecting voice in a mixture of sound sources remains a challenging task in MIR research. The musical content can be perceived in many different ways as instrumentation varies. We evaluate how instrumentation affects singing voice detection in pieces using a standard spectral feature (MFCC). We trained Random Forest models with song remixes for specific subsets of sound sources, and compare it to models trained with the original songs. We thus present a preliminary analysis of the classification accuracy results.

Palavras-chave: Digital Sound Processing, Music Analysis and Synthesis, Music Information Retrieval

Referências

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Publicado
25/09/2019
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MOURA, Shayenne; QUEIROZ, Marcelo. Instrumental Sensibility of Vocal Detector Based on Spectral Features. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO MUSICAL (SBCM), 17. , 2019, São João del-Rei. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 212-214. DOI: https://doi.org/10.5753/sbcm.2019.10451.