Abstract
Every Carnatic music concert is made up of many musical items. Every musical item has a lyrical composition (kriti) which can be optionally preceded by an ālāpanā segment. The duration of the ālāpanā along with the rāgā in which the ālāpanā has been rendered is a strong indication of an artist's creativity and musical knowledge. Hence automatic segmentation of an item to extract the ālāpanā segment is of great value in qualitative assessment of a concert. Segmenting a musical item into ālāpanā and kriti has applications in musical retrieval. To find the boundary between ālāpanā and kriti, KL2 distance on Cent Filterbank Energy feature is used that locates change in timbre property. A GMM is used to verify the boundary. To further improve the accuracy of segmentation, rules based on musical domain knowledge are automatically applied. Using this approach a frame-level accuracy of 91.34% was obtained.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
