International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 127 - Number 14 |
Year of Publication: 2015 |
Authors: Kunjal Gajjar, Siddhi Shah |
10.5120/ijca2015906505 |
Kunjal Gajjar, Siddhi Shah . Mood based Playlist Generation for Hindi Popular Music: A Proposed Model. International Journal of Computer Applications. 127, 14 ( October 2015), 11-14. DOI=10.5120/ijca2015906505
Large digital databases of Hindi music are available which creates an opportunity of filtering this data with multiple parameters. One of the most important parameter used by the listeners are their moods. This paper focuses on Automatic generation of mood based playlist for Hindi popular music with minimum user intervention. There are two major modules of the proposed system. The first module identifies user’s mood based on the inputs from social media and messaging app like WhatsApp. The second module is responsible for tagging the songs of available database. Tagging is done on the basis of Genre, Artists, Tempo and Lyrics. Using the above mentioned modules, mood based playlist can be generated for user.