You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Is your feature request related to a problem? Please describe.
I'm always frustrated when I can't find the right music to match my mood. Users of the "ThereForYou" app may experience similar frustration when looking for music that can help improve or support their current emotional state. Finding the right music can be a powerful tool for managing stress, lifting mood, or calming anxiety, but manually searching for appropriate tracks can be time-consuming and ineffective.
Describe the solution you'd like
I would like to see a mood-driven music recommendation system integrated into the "ThereForYou" app. This feature would analyze users' emotional check-ins and suggest music tracks or playlists that align with their current mood. For example, if a user is feeling stressed, the system could recommend calming music, while an upbeat playlist could be suggested if a user is feeling happy. This personalized approach would help users manage their mental health more effectively through music.
Describe alternatives you've considered
Manual Playlist Creation: Users create their own playlists for different moods, but this requires significant effort and may not be as effective as an automated system.
Third-Party Music Apps: Users use external music apps with mood playlists, but these are not integrated with their emotional check-ins and may lack personalization.
Generic Recommendations: Providing generic music recommendations based on popular mood playlists, but these lack the personalization that would make the feature more effective.
Additional context
Integrating a mood-based music recommendation system could enhance the overall user experience of the "ThereForYou" app. By providing personalized music suggestions, we can offer a more holistic approach to mental health support. This feature can leverage existing music APIs, such as Spotify's, to access a wide range of tracks and ensure that recommendations are relevant and up-to-date.
Hey @TAHIR0110 kindly look into this issue and allow me to work on this under GSSoC '24.
Thanks.
The text was updated successfully, but these errors were encountered:
Hi there! Thanks for opening this issue. We appreciate your contribution to this open-source project. We aim to respond or assign your issue as soon as possible.
Is your feature request related to a problem? Please describe.
I'm always frustrated when I can't find the right music to match my mood. Users of the "ThereForYou" app may experience similar frustration when looking for music that can help improve or support their current emotional state. Finding the right music can be a powerful tool for managing stress, lifting mood, or calming anxiety, but manually searching for appropriate tracks can be time-consuming and ineffective.
Describe the solution you'd like
I would like to see a mood-driven music recommendation system integrated into the "ThereForYou" app. This feature would analyze users' emotional check-ins and suggest music tracks or playlists that align with their current mood. For example, if a user is feeling stressed, the system could recommend calming music, while an upbeat playlist could be suggested if a user is feeling happy. This personalized approach would help users manage their mental health more effectively through music.
Describe alternatives you've considered
Additional context
Integrating a mood-based music recommendation system could enhance the overall user experience of the "ThereForYou" app. By providing personalized music suggestions, we can offer a more holistic approach to mental health support. This feature can leverage existing music APIs, such as Spotify's, to access a wide range of tracks and ensure that recommendations are relevant and up-to-date.
Hey @TAHIR0110 kindly look into this issue and allow me to work on this under GSSoC '24.
Thanks.
The text was updated successfully, but these errors were encountered: