Mit der ElevenLabs API eigene Hoerbuecher automatisch erstellen

If you’ve ever wanted to turn a pile of markdown files, PDFs, or plain‑text stories into a polished audiobook, you’re not alone. Traditional TTS engines either sound robotic or require a costly subscription. Enter ElevenLabs, a modern voice‑AI platform that delivers natural‑sounding speech and even lets you clone a voice with just a few minutes of audio. In this walkthrough we’ll build a simple, extensible audiobook generator using the ElevenLabs API. By the end you’ll have a script that can:

All of this can be done with just a few lines of Python (or a curl command if you prefer the command line).

Before we dive into code, make sure you have:

If you don’t have an API key yet, head over to the ElevenLabs sign‑up page and grab one. The affiliate link below works for anyone signing up for the first time:

export ELEVENLABS_API_KEY = "your-secret-key-here" Enter fullscreen mode Exit fullscreen mode Keeping the key out of source control is a best practice, especially if you plan to share the repo.

If you just want to see the magic in action, fire off a single request with curl. Replace YOUR_VOICE_ID with the voice you’d like to use (the default “Rachel” works fine for demos).

curl -X POST "https://api.elevenlabs.io/v1/text-to-speech/YOUR_VOICE_ID" \ -H "xi-api-key: $ELEVENLABS_API_KEY " \ -H "Content-Type: application/json" \ -d '{ "text": "Hello, world! This is a quick test of the ElevenLabs text‑to‑speech API.", "voice_settings": { "stability": 0.75, "similarity_boost": 0.85 } }' \ --output test_output.mp3 Enter fullscreen mode Exit fullscreen mode Open test_output.mp3 in your favourite player – you should hear a surprisingly human voice reading the sentence.

Below is a minimal Python wrapper that handles authentication, sends the request, and writes the MP3 to disk.

import os import requests API_URL = " https://api.elevenlabs.io/v1/text-to-speech " API_KEY = os. getenv ( " ELEVENLABS_API_KEY " ) VOICE_ID = " YOUR_VOICE_ID " # e.g., "EXAVITQu4vr4xnSDxMaL" def synthesize ( text: str, out_path: str ): headers = { " xi-api-key ": API_KEY, " Content-Type ": " application/json " } payload = { " text ": text, " voice_settings ": { " stability ": 0.75, " similarity_boost ": 0.85 } } response = requests. post ( f " { API_URL } / { VOICE_ID } ", json = payload, headers = headers ) if response. status_code!= 200: raise Exception ( f " API error { response. status_code }: { response. text } " ) with open ( out_path, " wb " ) as f: f. write ( response. content ) if __name__ == " __main__ ": sample = " It was the best of times, it was the worst of times... " synthesize ( sample, " chapter1.mp3 " ) Enter fullscreen mode Exit fullscreen mode Run the script and you’ll get chapter1.mp3. Swap out the sample variable with any text you like.

Audiobook chapters often exceed the 2 KB limit imposed by the API per request. The recommended approach is to:

Here’s a helper that does the heavy lifting:

import textwrap from pydub import AudioSegment def split_text ( text, max_chars = 500 ): # Simple split on newline, then wrap long paragraphs paragraphs = text. split ( " \n " ) chunks = [] for para in paragraphs: if not para. strip (): continue wrapped = textwrap. wrap ( para, width = max_chars ) chunks. extend ( wrapped ) return chunks def generate_chapter ( text, out_file ): chunks = split_text ( text ) temp_files = [] for i, chunk in enumerate ( chunks ): tmp = f " tmp_ { i }.mp3 " synthesize ( chunk, tmp ) temp_files. append ( tmp ) # Concatenate all temporary MP3s combined = AudioSegment. empty () for tmp in temp_files: combined += AudioSegment. from_mp3 ( tmp ) combined. export ( out_file, format = " mp3 " ) # Clean up temporary files for tmp in temp_files: os. remove ( tmp ) # Example usage: if __name__ == " __main__ ": with open ( " my_book_chapter.txt ", " r ", encoding = " utf-8 " ) as f: chapter_text = f. read () generate_chapter ( chapter_text, " chapter1_full.mp3 " ) Enter fullscreen mode Exit fullscreen mode The split_text function respects natural paragraph breaks, which helps preserve intonation cues for the model.

ElevenLabs also offers a voice cloning endpoint that lets you upload a few minutes of a speaker’s audio and generate a custom voice ID. The flow is:

Because cloning can be a whole tutorial on its own, we’ll just point you to the official docs and encourage you to experiment once you’re comfortable with the basics.

If you want to expose the generator as a tiny web service (e.g., for a personal website), Flask or FastAPI make it painless:

from fastapi import FastAPI, HTTPException from pydantic import BaseModel app = FastAPI () class TTSRequest ( BaseModel ): text: str voice_id: str = " YOUR_DEFAULT_VOICE_ID " @app.post ( " /tts " ) def tts ( req: TTSRequest ): try: out_path = " output.mp3 " synthesize ( req. text, out_path ) return { " audio_url ": f " /static/ { out_path } " } except Exception as e: raise HTTPException ( status_code = 500, detail = str ( e )) Enter fullscreen mode Exit fullscreen mode Run uvicorn myservice:app --reload and you have a REST endpoint that any front‑end can hit. Remember to serve the static/ folder so the MP3 files are reachable.

From here you can add features like chapter metadata, cover art embedding (via ID3 tags), or even a simple CLI that reads a folder of.txt files and spits out a full audiobook package.

The ElevenLabs API makes high‑quality, natural‑sounding narration accessible to any developer. Whether you’re building a personal project, a SaaS product, or just having fun with voice AI, the platform’s generous free tier and straightforward REST interface are perfect for rapid prototyping.

👉 Ready to give it a spin? Grab your ElevenLabs API key now: https://try.elevenlabs.io/kr07zfuqn1bp

Happy coding, and enjoy listening to the stories you bring to life!