JaCappella Corpus: A Japanese a Cappella Vocal Ensemble Corpus
This provides a domain-specific dataset for vocal ensemble separation, targeting researchers in music information retrieval, but it is incremental as it builds on existing vocal ensemble datasets by adding genre variety and specific voice parts.
The authors constructed the jaCappella corpus, a dataset of 35 Japanese a cappella vocal ensemble songs with individual voice part recordings, to address vocal ensemble separation and synthesis. Experimental evaluation shows it is a challenging resource for this task.
We construct a corpus of Japanese a cappella vocal ensembles (jaCappella corpus) for vocal ensemble separation and synthesis. It consists of 35 copyright-cleared vocal ensemble songs and their audio recordings of individual voice parts. These songs were arranged from out-of-copyright Japanese children's songs and have six voice parts (lead vocal, soprano, alto, tenor, bass, and vocal percussion). They are divided into seven subsets, each of which features typical characteristics of a music genre such as jazz and enka. The variety in genre and voice part match vocal ensembles recently widespread in social media services such as YouTube, although the main targets of conventional vocal ensemble datasets are choral singing made up of soprano, alto, tenor, and bass. Experimental evaluation demonstrates that our corpus is a challenging resource for vocal ensemble separation. Our corpus is available on our project page (https://tomohikonakamura.github.io/jaCappella_corpus/).