It was the first autumn that I went to New York City. I was sitting by the window of the school bus while it traveled from Brooklyn to Manhattan, listening to the music. When the bus passed the Manttanbrige, the view through the window was turning from vast and panoramic Manhattan urban to vibrant and old-timey Chinatown. Suddenly, the song playing in my ears was accidentally changed to Yumeji’s Theme which is the theme song of Wong Kar-wai’s In the Mood for Love. It hit me at the moment as if I was in Hong Kong in the 60s instead of New York City. Seeing the traffic flowing and people coming and going through the window, listening to the old song, and imagining being in Wong Kar-Wai’s film, I decided that’s my song for Chinatown.
Through that unforgettable experience, I wonder if I can experience this everywhere in the city. What if I can have a music player that plays music, particularly for the location that I am being while I am wandering and exploring in the city? Then here comes the idea and concept of the app Music Map.
Music map is a music player application whose recommendation algorithms are based on your real-time geolocation. The algorithm will make you a personalized playlist based on your current location. The song selection is based on the history, culture, and people at the current location. We would like to bring you a more immersive and bonded experience with you and your city.
Location-based Music Recommendation
Playlist changes while waking in different zones of the city
Computer Scientists have been working on recommendation algorithms and systems for many years. To enhance user’s experience of music navigation, discovery, sharing, scientists raised the concept of context-aware music recommender systems that are capable of suggesting music items taking into consideration contextual conditions, such as the user’s mood or location. Specifically, Matthias Braunhofer, Marius Kaminskas and Francesco Ricci conduct research on creating a context-aware music recommendation system based on selecting music content that fits a place of interest (POI). In their research, it shows that users judge the recommended music as suited for the POIs, and that the music is rated higher when it is played in this usage scenario. That means, it is viable and suitable to implicate this algorithm in making a unique experience between the audience and the city. While in the music map, the recommendation system will be based on the real time location to recommend music from all over the city.
In Spotify - Tag Your Tracks, François Hulet offered a UX idea of an additional function to spotify making people accessible to share each other's music based on their location. The idea of building the bonds between listeners and location is similar, while Tag Your Tracks mainly focus on the interpersonal interaction, while Music Map cares about your personal experience with the city’s cultural background and history
In my final project I will make an interactive art installation called Malèna. Malèna is coming from a famous film called Malèna, and it tells a story in Italy about a beautiful woman called Malèna being judged, discriminated and insulted by all of the people in the town just because she is prettier than other women in the town. This film shows the malignity and prejudice of society to a helpless woman. I want to make a installation that shows the labels that the society puts on women, actually, any girl is Malèna to some degree. So I named my project Malèna.
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Location-based Music Recommendation
Playlist changes while waking in different zones of the city.
To Keep the simplicity of the app, I only kept the most basic function of a music app. Becasue I wanted the user to enjoy music the most, instead of being bizzard by the buttons of unnecessary functions.
To let the users have a better actions toward different bottons, I add the press animation of each botton, so that the user could know where to press and how to interact.
