Extracting music genes for era classification

• A method for classification of music feature is proposed.
• Music gene provides a higher level of music feature and maintains the integrity of melody.
• Performance demonstrates that genes are more meaningful compared to the previous proposed motifs.

With the growth of computational culture, the concept of cultural syntactic unit has been investigated quite intensively in recent years. The existing approaches of extracting music feature always consider putting notes together according to certain rules. However, sometimes, it might be better take the integrity of melody into account. In this paper, we introduce a syntactic unit named music gene and propose a music feature extraction method for era classification. Music genes are extracted from XML files and estimated utilizing their intervals to investigate their representation of music feature. We evaluate the performance of music gene and the previous proposed motif to illustrate the effectiveness of music gene in classification. Support vector machines are applied to classify XML files into their respective classes by learning from training data. We obtain the classification accuracy for a collection of 764 music genes, demonstrating that significant classification can be achieved using higher level music feature.