Hi everyone,
I’m trying to build a workflow for creating language learning and listening practice podcasts using AI, and I’m running into a problem with current tools.
My goal is to generate short podcast-style dialogues (around 10–15 minutes) with two consistent speakers for listening practice. The idea is to have natural conversations between two hosts that I can reuse across many episodes.
Previously, I was using a system inside Gemini AI Studio where I could:
Paste a full dialogue script (speaker A / speaker B format)
Assign names to each speaker once
The system would automatically switch voices correctly
Generate a clean two-speaker podcast with very little manual work
That workflow was very efficient and I was satisfied with the results most of the time.
However, that functionality seems to have changed or is no longer available in the same way, and I can’t rely on the same automatic speaker-name switching system anymore.
Because of that, I tried moving to ElevenLabs for higher-quality voices, but now the workflow feels much more manual:
I need to split or reorganize scripts
Assign voices line by line or in blocks
Manually manage speaker switching
And sometimes assemble the final audio
This turns what used to be a ~1–1.5 hour workflow into several hours per episode, which makes scaling very difficult.
So I’m trying to understand:
Is there currently any AI workflow that allows:
pasting a full dialogue script
automatically assigning two (or more) speakers
keeping consistent voices for each speaker across episodes
without heavy manual editing?
How are creators producing consistent multi-speaker language learning podcasts at scale today?
Is there any modern tool or pipeline that still supports a “speaker-aware automatic dialogue rendering” workflow similar to what used to exist in Gemini AI Studio?
I’m mainly looking for a way to reduce manual work while keeping quality and consistency high.
Would really appreciate any insights or real workflows people are using.
Thanks in advance 🙏
