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Music Player with Smart Song Ranking
Richter, Roman ; Szőke, Igor (referee) ; Herout, Adam (advisor)
The goal of my thesis is to create full-featured off-line music player for Android, which main feature is monitoring and storing data of user actions during the music playback. Every song has score, that is calculated from this data. The bigger the score is, the bigger is the chance for playing the song. This functionality is implemented by two coherent algorithms - the ranking algorithm and the algorithm for the song selection. Graphical user interface allows immediate start of playback and its easy control. My work is targeted at the users, who have music stored on their mobile devices. The purpose of this application is to help them to sort their favorite songs from those less favorite and play them according to that. The application is especially useful to those users, who actively use playback control on headphones or on another remote control.
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Innovative Music Player for Smartphones and PC
Richter, Roman ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
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.
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Innovative Music Player for Smartphones and PC
Richter, Roman ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
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.
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Music Player with Smart Song Ranking
Richter, Roman ; Szőke, Igor (referee) ; Herout, Adam (advisor)
The goal of my thesis is to create full-featured off-line music player for Android, which main feature is monitoring and storing data of user actions during the music playback. Every song has score, that is calculated from this data. The bigger the score is, the bigger is the chance for playing the song. This functionality is implemented by two coherent algorithms - the ranking algorithm and the algorithm for the song selection. Graphical user interface allows immediate start of playback and its easy control. My work is targeted at the users, who have music stored on their mobile devices. The purpose of this application is to help them to sort their favorite songs from those less favorite and play them according to that. The application is especially useful to those users, who actively use playback control on headphones or on another remote control.
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