Algorithms that can understand and interpret characteristics of music, and organise them for and recommend them to their users can be of great assistance in handling the ever growing size of both private and commercial collections.
Music is an inherently multi-modal type of data, and the lyrics associated with the music are as essential to the reception and the message of a song as is the audio. In this paper, we present advanced methods on how the lyrics domain of music can be combined with the acoustic domain. We evaluate our approach by means of a common task in music information retrieval, musical genre classification. Advancing over previous work that showed improvements with simple feature fusion, we apply the more sophisticated approach of result (or late) fusion. We achieve results superior to the best choice of a single algorithm on a single feature set.