Synesthesia

Fourth feature: Find Your Flow
Main feature: Discover your sound
Third feature: Nearby Music
Main feature: The result
Second feature: Search Music

Inspiration

Music has the ability to connect us to places, people, objects, and experiences. A photograph, while voiceless, may evoke a particular sound, a city landscape can have its own artistic atmosphere, and a familiar song may bring back a distant memory.

We created Synesthesia to make these connections easier to discover. Initially, our idea focused on helping users discover music through their surroundings, either by analyzing photographs or exploring the musical history of geographical locations.

As our idea developed, we realized that the streets we walk, the places we visit, and the memories we create can hold both shared and personal glimpses of the human experience—glimpses worth preserving.

Our goal became creating a platform that connects music, places, and memories in ways traditional music recommendation services do not.

What it does

Synesthesia combines artificial intelligence, geographical exploration, and community storytelling to offer a unique music discovery experience.

Photo-Based Discovery: Users capture or upload photographs and receive music recommendations based on the atmosphere and visual elements of the image.

Location-Based Discovery: Users explore music and artists associated with geographical locations anywhere in the world.

Find Nostalgia: A dedicated feature that focuses on discovering vintage music and historical musical connections.

Community Archive: Users can share location-based stories, documented musical history, and personal memories connected to songs and places.

Flow: A personalized music station that considers users' favorite songs, local time, and weather conditions.

Rather than relying entirely on listening history, Synesthesia encourages users to discover music through their surroundings and experiences.

How we built it

We developed Synesthesia using two primary technical approaches: visual-context analysis and geographical-context discovery.

For photo-based discovery, we integrated AI-powered image analysis to interpret visual elements such as scenery, atmosphere, and mood. These characteristics are then used to identify suitable musical genres and generate relevant song recommendations.

For location-based discovery, we designed an experience that connects geographical locations with their musical backgrounds, including associated artists, genres, and cultural history.

We also incorporated user accounts and database functionality to support personalized experiences, such as saving favorite songs and previously analyzed moments.

Our overall approach combines AI-generated recommendations with location-based exploration, creating opportunities for users to discover music through multiple perspectives.

Challenges we ran into

One of our biggest challenges was distinguishing AI-generated recommendations from verified musical history.

Although AI can recommend music that matches the atmosphere of an image or location, these suggestions do not necessarily represent historically accurate relationships between songs and places.

We addressed this challenge by developing the concept of separating documented musical history, geographical music origins, and personal memories into distinct categories.

Another challenge involved connecting multiple technical components, including AI analysis, music recommendation APIs, and database management, while keeping the user experience consistent.

We also needed to ensure that personal information, saved recommendations, and user preferences remained associated with the correct accounts.

Accomplishments that we're proud of

One of our proudest accomplishments is developing a working AI-powered music discovery experience that transforms real-world visual information into personalized music recommendations.

We successfully integrated photo and video analysis with music discovery, allowing users to capture their surroundings and receive songs that reflect the atmosphere of those moments.

We also implemented user authentication and database functionality, enabling users to maintain personal collections of mood analyses and favorite songs.

Beyond the technical implementation, we are proud of expanding our initial idea into a broader vision that connects music discovery with cultural exploration, nostalgia, and personal storytelling.

Synesthesia demonstrates how everyday experiences can inspire new ways to discover and appreciate music.

What we learned

Throughout this project, we learned that music discovery can be much more than finding a new song.

We gained experience integrating artificial intelligence with external APIs, managing user data, implementing authentication, and developing features that connect different technologies into a unified application.

We also learned the importance of distinguishing verified information from AI-generated suggestions, particularly when presenting historical or cultural content.

Most importantly, this project helped us understand how technology can strengthen the relationship between music and human experiences by connecting songs with meaningful places, moments, and memories.

What's next for Synesthesia

Our next goal is to expand Synesthesia beyond photo-based recommendations into a more comprehensive music discovery platform.

We plan to continue developing location-based discovery, allowing users to explore music associated with cities, landmarks, and culturally significant places around the world.

We also want to expand Find Nostalgia, helping users rediscover vintage music and explore the musical history of different generations.

Another major goal is to develop the Community Archive, where users can contribute personal stories, document musical connections, and preserve memories associated with specific locations.

Finally, we aim to improve Flow, our personalized listening experience, by incorporating favorite songs, weather conditions, and time of day to create playlists that adapt to each user's environment.

Our long-term vision is to make Synesthesia a platform where discovering music also means discovering the stories, cultures, and memories behind it.