Song Recommendation for Social Singing Community

Nowadays, an increasing number of singing enthusiasts upload their cover songs and share their performances in online social singing communities. They can also listen and rate other users' song renderings. An important feature of the social singing communities is to recommend appropriate singing-songs which users are able to perform excellently. In this paper, we propose a singing-song recommendation framework to make song recommendation in social singing community. Instead of recommending songs that people like to listen, we recommend suitable songs that people can sing well. We propose to discover the song difficulty orderings from the song performance ratings of each user. We transform the difficulty orderings into a difficulty graph and propose an iterative inference algorithm to make singing-song recommendation on the difficulty graph. The experimental result shows the effectiveness of our proposed framework. To the best of our knowledge, our work is the first study of singing-song recommendation in social singing communities.