Spotify MEM is an enhanced Spotify player that lets you utilize the memorabilia powers of music. It will do this by showing the user’s memories correlated with the song which is currently playing on spotify, as opposed to look at the album cover created by the artist.
I often listen to songs and artists in chunks of time. As an example, I listened to Black Eyed Peas a lot in September of 2021, not so much anymore. Spotify MEM will show me a photo from my camera roll from September 2021 when I listened to Black Eyed Peas!
Name: Lars Østberg Moan
Student number: 48270645
Spotify MEM is going to deliver an enhanced listening experience. It will do this by seamlessly showing you connected memories from your camera roll while you are listening to your favorite music on Spotify.
If you happened to be traveling while finding the song you are now listening to, Spotify MEM will also graphically show you an overview of where in the world you were when you found that very song.
The complete finished product will do this by both integrating the Spotify API and authorizing access to the user’s personal photos.
The form factor of the finished product will be an iPhone widget, similar to the stock photo-widget but with a magic connection between content being played and the photo.
Image throwback: The magic of the product lies in the matchmaking of your photos and your personal listening history on Spotify. This matchmaking is the most essential part of the project, as the user is supposed to create a real emotional relation to the product via memory throwbacks.
Location throwback: We often find new music while traveling. Spotify MEM is going to utilize this connection by having the ability to also show an overview of your travel in the widget.
MVP of Spotify MEM will include:
Basic song -> photo matchmaking: The initial solution will not use machine learning approaches to this matchmaking but rather quite “simple” statistics.
Showcasing the currently playing song: Users need to also see the currently playing song and not only the photo. Spotify’s API will be used for this.
The key quality attributes that need to be fulfilled for Spotify MEM to be a success are:
Availability: It is crucial that the service is always available for the user. The goal is that users of Spotify MEM will use it whenever they listen to music, which is very often. It is therefore considered crucial that the service is always available.
Security: The service will make use of very personal user data. Especially related to the user’s photos. Security will therefore be an extra important attribute for Spotify MEM compared to other services.
Reliability:** It is critical for the service that the matchmaking between the songs played and photos are reliable. In the sense that the user doesn’t get any unexpected matches. The service is based upon creating an emotional connection between the user’s very personal songs and photos. The service’s success is therefore closely connected with creating trust with the user.
Availability: This will be evaluated by extensive testing of the service related to uptime and responsiveness during max load.
Security: This attribute will be evaluated by creating an extensive test of attacks that the service might meet. By constantly testing the service against these attacks and patching the possible security holes, the service will improve its security over time.
Reliability: This attribute is going to be evaluated by having the users submit whether or not a song -> photo match was considered good or not. It can be considered as continous user testing.