A team of music technology students developed a system to enable novices to create remixes of any 4 Spotify songs they want. The system uses source separation to break down the songs into different components, such as vocals, drums, bass. Users can then generate 32 bar compositions that randomize how the song is constructed. The goal is to better understand users' preferences for control vs. automation of their mashups.
As event sequence data grow in prominence, sequential pattern mining algorithms have been widely adopted to discover interesting patterns in data. For instance, ecommerce websites use these algorithms large-scale clickstream data to understand the common paths taken by customers. In the healthcare domain, sequential pattern mining algorithms open the door to investigating the sheer volume of patients in a hospital.
Visualization Journalism is focused on developing an interface and graphical metalanguage for massive multimodal news datasets. Such datasets are increasingly available, but for copyright reasons, they cannot be made entirely open to the public. The project seeks to offer an abstracted and legal representation of news data, to enable comparative, cooperative and computer-supported analysis of trends across news events and networks.
GVU Resource Labs
Built for Success
A mobile computing "hackerspace."
Visit the App Lab website
Location: TSRB 333
GVU Prototyping Lab
From Concept to Creation
A rapid prototyping "makerspace."
Visit the Prototyping Lab website
Location: TSRB Basement
GVU Craft Lab
Making for All
A soft-goods "makerspace."
Visit the Craft Lab website
Location: TSRB 225B
Testing Methods and Technology
An adaptable project testing space.
Visit the Usability Lab website
Location: TSRB 216