SplitPost

SplitPost converts written blog entries into audio or video pieces that match the style and tone of the original author. It analyzes each line of the source text and applies user‑defined voice rules, ensuring the generated output reflects the writer’s unique phrasing and cadence rather than a generic AI voice. The tool is targeted at creators who want to reuse their existing articles on platforms that favor native‑style media, such as social feeds or podcasts, without losing their personal voice.

The system operates by parsing the input post, mapping the content to a format suitable for the target platform, and then synthesizing spoken or visual elements that adhere to the specified voice constraints. Because the voice enforcement is applied on a per‑line basis, the resulting media retains the nuances of the original writing while fitting the conventions of the destination channel.

As an experimental project, SplitPost is positioned for users comfortable with early‑stage software who need a straightforward way to repurpose textual material into platform‑native formats that sound authentically like the author.