janpmz

This is very fresh, you can add features is you like.

I've made a version of it you can listen to: https://pdftomp3.com/player.html?example_id=6ad14c5229ba4da7...

The experience has been improved now!

I've updated my video to show the player experience and the quality of the voices:

https://youtu.be/1qiH_SeDyyc

Here you go my friend, a two speaker podcast in Thai :)

https://pdftomp3.com/published/player.html?publication_id=6a...

Its about the whole pipeline. From adding a PDF to listening in the car (with the app).

It handles the formatting of scientific papers very well. E.g. I can exclude footnotes etc. But I didn't test it much with tables yet.

Here you can listen to examples: https://pdftomp3.com/examples/

Via MCP more voices are available (all OpenAI and Gemini voices, depending on which api key you use).

I did both of that too! At the end I made my own app to listen to the episodes.

Thanks! Currently, I'm using Gemini TTS and Kokoro TTS as a free option. Kokoro is fast and I can run it on my own server, but I'm not using it as a standard yet because Gemini supports more languages and has more voices available. But text-to-speech processing is the biggest bottleneck at the moment.

There are two parts to the processing. The processing of the document itself is done on your OpenAI/Codex subscription. Additionally, you have to submit an API key for the text-to-speech processing. There you can use a Gemini key or an OpenAI key.

The diffusion codes all have a distinctive style where the qr code "melts" into the picture. I wanted to have more dedicated codes.

With simple prompting it works sometimes but less reliably. I implemented a healing and strengthening algorithm which can improve codes that don't scan quickly.

Thanks! Links are one cards and on the episode pages too.

Ok, thanks for the viewpoint, that makes sense. I use AI summaries every day and find it very valuable. But I also see the trend e.g. on Reddit, that people are very dismissive of ai content.

Both Text-to-Speech and Speech-to-Text now have local models that are good enough to get the job done. Kokoro for TTS, Parakeet for STT and Fluid-1 for text formatting (I use it with FluidVoice). I hope this is a trend that continues for other applications.

Isn't the EU rather like a single point of failure?

I wonder if they also have a seeker pointed at my face then, because I don't want that shining into my eyes.

Why do I get downvoted whenever I post something here? Do you think its too spammy? Because its AI? Do I have a downvote bot following me?

After seeing this for the first time, I've build PdfToMp3 to listen to these papers. It has now evolved into ListenDock. Fun fact: PdfToMp3 existed before NotebookLM and I already had "overviews", but I called them teacher explanations.

Here is an example of a "Teacher Explanation" of the paper "Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton"

https://listendock.com/e/quantifying_the_rise_and_fall_of_co...

> If they diverge

This is the key, if they are very similar but used by different consumers the chance that they will diverge in the future is very high. And once they do they will break the abstraction.

Don't show this to the EU, or they will force us drink only ultrasound espresso from now on.

I've been building a PDF -> MP3 tool (web, iphone, android): https://listendock.com/

Then a little calorie-radar-alert app that motivates you to stay on diet before going into a shop: https://apps.apple.com/us/app/stay-lean-calorie-navigation/i...

And to test the hypothesis if the motivation actually works with "fast flashing images" I built this experiment: https://fitfatflix.fit/

When openClaw came out I build a game like map around it to orchestrate tasks: https://memefields.com/

And not published, I build a little recommender app of activities I can do only today or only this time of the year where I currently am, so I don't miss good things.

And some other stuff I'm working on right now :)

You know what would be cool, a "different suggest" that acts like different algorithm.

I had fun making this :)

I was concerned about big players offering the same functionality when building listendock.com, but maybe there is a place for specialized apps like that.

My vibe coding playlist: https://youtube.com/playlist?list=PLFcwd2lzu8tujlF-tPg1EfXPU...

Lately I've been trying to learn about topics more intentionally instead of following what the YouTube feed recommends, for example evolutionary algorithms. For that I built the topics feature in my app, so I get a number of papers and articles suggested and then over the next weeks I can listen to them.

A lot of this goes away when the person who builds also decides what to build.

Hey, this is my highly experimental project. I’m curious to see the first reactions.