Year: 2019
Type: article
Abstract: In the field of audio classification, audio signals may be broadly divided into three classes: speech, music and events. Most studies, however, neglect that real audio soundtracks can have any combination of these classes simultaneously. In this study, a novel feature, “Entrocy”, is proposed for the detection of music both in pure form and overlapping with the other audio classes. Entrocy is defined as the variation of the information (or entropy) in an audio segment over time. Segments which contain music were found to have lower Entrocy since there are fewer abrupt changes over time. We have also compared Entrocy with existing music detection features and the entrocy showing a promising performance. Keywords—Music detection, audio content analysis, audio indexing, Entropy, real world audio classification.
Institutions: Iraqi University, University of Diyala, University of Salford
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2969907289