narrating your blog with local AI

A friend who drives a lot asked if there was an audio version of my posts. There wasn’t. So I looked into it — and it turned out to be absurdly easy.

The whole thing took an evening. That’s the part worth writing about.

Open-source text-to-speech crossed a quality threshold sometime in 2025, and I completely missed it. Kokoro-82M¹ is 82 million parameters — tiny — Apache 2.0 licensed, and it sounds good enough that I had to double-check I wasn’t accidentally using a paid API. On an M4 MacBook it generates 15 minutes of audio in about 60 seconds. Chatterbox by Resemble AI beat ElevenLabs in blind listening tests. Multiple open models now compete with the proprietary leaders. This happened fast.

what I built

I wrote a small tool called blog-narrator that adds “listen to this post” audio to Jekyll blogs. It strips markdown to clean narration text,² generates speech locally via Kokoro through mlx-audio on Apple Silicon, and embeds a minimal audio player that shows up on posts that have audio. No API keys, no cloud, no cost.

The workflow: write your post, run narrate _posts/your-post.md, commit, push. Done.

What strikes me isn’t the technology — it’s the ratio. An evening of work, zero ongoing cost, and every post on my blog now has a listenable version. A year ago this would have required an API subscription, careful rate limiting, probably a CI pipeline. Now it’s a Python script and a Jekyll include.

I keep noticing this pattern. Things that used to require real infrastructure quietly becoming a single local command. Not because someone built a product for it, but because the underlying models got good enough that you can just wire them up yourself. The fruit hangs so low now that it feels irresponsible not to pick it.

setup

If you want to add this to your Jekyll blog:

pip install git+https://github.com/galsapir/blog-narrator.git

Copy the audio player include to your _includes/ directory, add one line to your post layout, create a narrate.yml config, and run narrate on your posts. The README has the full details.

Requires macOS with Apple Silicon, Python 3.10+, and ffmpeg.