Interaction designers often use machine learning tools to generate intuitive mappings between complex inputs and outputs. These tools are usually trained live, which is not always feasible or practical. This prototype aims to facilitate the training and testing of Interactive Machine Learning (IML) models, by providing easy access to datasets stored on an online repository.
This prototype combines RepoVizz, an online repository and visualizer for multimodal data, with the Interactive Machine Learning (IML) software Wekinator, to demonstrate a technical solution for prototyping multimodal interactions that decouples the data acquisition step from the model training step. This way, different input data set-ups can be easily replicated, shared and experimented upon their capability to control complex output without the need to repeat the technical set-up.