Abstract
How useful are topic models based on song lyrics for applications in music information retrieval? Unsupervised topic models on text corpora are often difficult to interpret. Based on a large collection of lyrics, we investigate how well automatically generated topics are related to manual topic annotations. We propose to use the kurtosis metric to align unsupervised topics with a reference model of supervised topics. This metric is well-suited for topic assessments, as it turns out to be more strongly correlated with manual topic quality scores than existing measures for semantic coherence. We also show how it can be used for a detailed graphical topic quality assessment.
Published Version (Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.