On Accuracy and Time Processing Evaluation of Cover Song Identification Systems

Autor(es)

Ferreira, Martha Dais ; Correa, Debora Cristina ; Grivet, Marcos Antonio ; dos Santos, Geovan Tavares ; de Mello, Rodrigo Fernandes ; Nonato, Luis Gustavo

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF NEW MUSIC RESEARCH; v. 45, n. 4, p. 333-342, DEC 2016.
• Citações Web of Science: 1

Resumo

Cover song identification (CSI) systems typically represent songs as chromagrams which are pairwise compared using different evaluation measurements. Chromagram comparison are usually computationally demanding, making most CSI systems unsuitable for real-world scenarios where millions of songs have to be processed. Evaluation mechanisms such as the ones proposed by Music Information Retrieval Evaluation eXchange (MIREX) handle MIR systems as black boxes, measuring their accuracy as a whole, thus disregarding the effectiveness of each particular component of the system. Moreover, computational times are usually not taken into account in the evaluation process, making difficult to assess the usefulness of the systems when facing large data-sets. In this manuscript, we present a systematic evaluation of the components of two state-of-the-art CSI systems that performed quite well according to MIREX. Our experiments indicate that the performance of those two systems strongly depends on the combination of the song descriptor and the comparison method used to quantify the similarity between songs. Nevertheless, the high computational cost involved in the comparison of song descriptors renders both approaches unfeasible to large data-sets, motivating the development of alternative methods. (AU)

• Processo FAPESP: 11/22749-8 - Desafios em visualização exploratória de dados multidimensionais: novos paradigmas, escalabilidade e aplicações
• Beneficiário: Luis Gustavo Nonato
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 14/13323-5 - Abordagem baseada na estabilidade de algoritmos de agrupamento de dados para garantir a detecção de mudanças de conceito em fluxos de dados
• Beneficiário: Rodrigo Fernandes de Mello
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 12/17961-0 - Mineração de Dados Musicais Baseada em Padrões Temporais
• Beneficiário: Débora Cristina Corrêa
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado