TextMixer: Writing via Sampling and Remixing

What if writers could sample and remix text as easily as musicians sample and remix audio? For musicians these activities are facilitated by sound banks, samplers, and digital audio workstations, but no analogous tools exist for text. In this work we introduce TextMixer, a system that leverages embedding search and large language models to support these sampling and remixing operations for text. Preliminary studies find that TextMixer reduces the friction for producing recombinatorial literature while helping users arrive at unexpected insights about their samples.