Singing Voice Detection in Electronic Music with a Long-Term Recurrent Convolutional Network

Singing Voice Detection (SVD) is a classification task that determines whether there singing voice in given audio segment. While current systems produce high-quality results on this task, the reported experiments are usually limited to popular music. A Long-Term Recurrent Convolutional Network (LRCN) was adapted detect vocals new dataset of electronic music evaluate its performance different genre and compare against those other state-of-the-art pop prove effectiveness across genre. Experiments two datasets studied impacts features block size LRCN temporal relationship learning, benefits preprocessing performance, generate benchmark intricacies.