HouseX: A Fine-grained House Music Dataset and its Potential in the Music Industry
Machine sound classification has been one of the fundamental tasks of music
technology. A major branch of sound classification is the classification of
music genres. However, though covering most genres of music, existing music
genre datasets often do not contain fine-grained labels that indicate the
detailed sub-genres of music. In consideration of the consistency of genres of
songs in a mixtape or in a DJ (live) set, we have collected and annotated a
dataset of house music that provide 4 sub-genre labels, namely future house,
bass house, progressive house and melodic house. Experiments show that our
annotations well exhibit the characteristics of different categories. Also, we
have built baseline models that classify the sub-genre based on the
mel-spectrograms of a track, achieving strongly competitive results. Besides,
we have put forward a few application scenarios of our dataset and baseline
model, with a simulated sci-fi tunnel as a short demo built and rendered in a
3D modeling software, with the colors of the lights automated by the output of
our model.