Reddit Text Cleaner — TTS-Ready Narration

Reddit Text Cleaner: turn a raw Reddit post into narration a voice can read

Paste a post body, or pipe a whole batch of them in, and you get back text a text-to-speech step can read straight off. Markdown gone, link syntax gone, the "Edit: thanks for the gold" trailer gone, and the result split into one segment per sentence.

It runs on fixed rules, not a model, so there is no key to supply and nothing to pay a model provider. That also means it is literal: it does what its lists say and nothing cleverer, and the places where that bites are written out below rather than left for you to find.

🧹 What Reddit Text Cleaner does

Four passes over each text. It strips markdown and link syntax down to plain words. It expands Reddit shorthand so a voice does not spell it out letter by letter, so AITA becomes "Am I the asshole" and MIL becomes "mother-in-law". It handles swearing the way you ask, from leaving it alone to removing it. Then it splits the result into sentences.

Each row also carries the numbers you need to decide whether a story fits a clip: word count, character count, sentence count, an estimated read time at your chosen speed, and a hook score out of 100 worked out from the opening sentence.

The texts array takes post objects as well as plain strings. It looks for scriptText, narration, selftext, body or text on each object, which means the output of the Reddit scraper linked below drops in without reshaping.

📥 What you give it

{
  "texts": [
    "AITA for leaving? **So** here's the _story_. Check [this](https://x.com).",
    "TIFU by replying all. Edit: yes I know."
  ],
  "profanityMode": "soft",
  "wpm": 150
}

Give it one or the other. A run with both text and texts empty fails rather than finishing with an empty dataset.

📤 What you get back

A real row from a real run:

{
  "ok": true,
  "original": "AITA for leaving? **So** here's the _story_. Check [this](https://x.com).\n\nEdit: thanks for the awards! TL;DR: I left.",
  "cleaned": "Am I the asshole for leaving? So here's the story. Check this.",
  "ttsSegments": [
    "Am I the asshole for leaving?",
    "So here's the story.",
    "Check this."
  ],
  "sentenceCount": 3,
  "wordCount": 12,
  "charCount": 62,
  "readTimeSeconds": 4.8,
  "hookScore": 64
}

🧾 Reading the output

Every row is a cleaned text and every row is charged. ok is always true, there are no sample rows and no diagnostic rows, and nothing is filtered out silently.

Two things do get dropped, and it is worth knowing which:

If the row count does not match what you sent, the first line is why.

▶️ How to run it

1. Open Reddit Text Cleaner and click Try for free. 2. Paste one post into Text, or put your batch into Texts. 3. Pick a Profanity handling mode. soft is the one to use for ad-safe voiceover. 4. Click Start. 5. Take cleaned or ttsSegments from the dataset, or read them from the API.

💰 How much does it cost?

$0.20 per 1,000 texts, which is $0.0002 each. Flat on every Apify plan, no volume tiers.

One text in, one row out, one charge. There is no model behind this and no key to add, so there is no separate provider bill on top.

💡 What people use it for

• Prepping Reddit stories for a faceless video pipeline, where markdown read aloud ruins the take.
• Making narration ad-safe in bulk with soft, instead of editing swearing by hand.
• Sorting a pile of candidate stories by hookScore and readTimeSeconds before picking the three

worth shooting.

• Turning long posts into per-sentence segments so captions line up with the audio.

🚧 What it does not do

• It does not remove emoji. Invisible zero-width characters go, visible emoji stay exactly where

they were. Strip them yourself if your voice reads them out.

• Abbreviation expansion is blunt. It matches shorthand without caring about case, so "5 mil"

comes out as "5 mother-in-law" and a name like Sil becomes "sister-in-law". If your text has ordinary words that look like Reddit shorthand, turn expandAbbreviations off.

• An Edit:, ETA: or PS: label cuts the rest. Everything from the first one of those to the

end of the text is removed, which is right for a thank-you trailer and wrong when the story keeps going after it.

• Sentence splitting is mechanical. An abbreviation with a full stop in it, like "Mr.", starts a

new segment.

• English only, and one fixed word list. No language detection, and you cannot supply your own

expansions or swaps.

• It does not fetch anything. Give it text. To pull the posts in the first place, use the

scrapers linked below.

🧭 Which Reddit actor do you need?

❓ Questions people ask

Does this call an AI model? No. It is rules and word lists, which is why there is no key field and why the output is the same every time you send the same text.

Can I feed it the Reddit Scraper's output directly? Yes. Put the rows into texts as they are. It reads scriptText, narration, selftext, body or text off each object.

Why is my read time wrong? It is word count against wpm, nothing more. Set wpm to the speed your voice actually reads at. A wpm of 0 gives you null rather than a number.

Is original the whole post? Only up to 4,000 characters. The cleaned field keeps the lot, so use that if length matters.

What does hookScore measure? How strong the first sentence looks as an opener, scored 0 to 100. It is a sorting aid for a batch, not a verdict.

🆘 If something breaks

Open the Issues tab on the actor page. Paste the text that came out wrong along with the run ID, and that is usually enough to see it.