  Lyrics transcription of polyphonic music is challenging not only because the
singing vocals are corrupted by the background music, but also because the
background music and the singing style vary across music genres, such as pop,
metal, and hip hop, which affects lyrics intelligibility of the song in
different ways. In this work, we propose to transcribe the lyrics of polyphonic
music using a novel genre-conditioned network. The proposed network adopts
pre-trained model parameters, and incorporates the genre adapters between
layers to capture different genre peculiarities for lyrics-genre pairs, thereby
only requiring lightweight genre-specific parameters for training. Our
experiments show that the proposed genre-conditioned network outperforms the
existing lyrics transcription systems.
