Year: 2018
Type: preprint
Abstract: Since the vocal component plays a crucial role in popular music, singing voice detection has been an active research topic in music information retrieval. Although several proposed algorithms have shown high performances, we argue that there is still room for improving the singing voice detection system. In order to identify the area of improvement, we first perform an error analysis on three recent singing voice detection systems. Based on the analysis, we design novel methods to test the systems on multiple sets of internally curated and generated data to further examine the pitfalls, which are not clearly revealed with the currently available datasets. From the experiment results, we also propose several directions towards building a more robust singing voice detector.
Source: arXiv (Cornell University)
Authors: Lee, Kyungyun, Choi, Keunwoo, Nam, Juhan
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Award: G4341594390
OpenAlex ID: W2806313776