The goal of this thesis is to create a music player for smartphones as well as PCs that works with local music files in the user's device and which can learn which songs does the user like based on their actions during listening to music. The music player can, among other things, remember which songs were skipped by the user, when was volume turned up, or how many times was a certain song played. Each song has a score that is calculated based on these actions. With a higher score, there is also a higher chance of playing the song in the future. The results of my thesis are two full-featured versions of music player, which are capable of communication with each other to ensure synchronization of song scores. The main benefit of this thesis is an improvement of user experience during listening to music, which is achieved by the application's algorithm for song selection and minimalistic user interface.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:445556 |
| Date | January 2021 |
| Creators | Richter, Roman |
| Contributors | Špaňhel, Jakub, Herout, Adam |
| Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.002 seconds