How to Reduce Audio Production Costs by 80% (using ElevenLabs & OpenAI)

Goal: Produce professional long-form audio (audiobooks/whitepapers) for a fraction of the cost by blending high-end and budget AI voices.

The Stack:

ElevenLabs: The “Hook” Engine (High Fidelity, Higher Cost).
OpenAI API: The Body Content Engine (High Volume, Low Cost).
Normalizer (Ensures consistent volume across both files).
- Shutter Encoder: The No-Code Normalizer (Visual tool for consistency).
- FFmpeg: The Command Line Normalizer (For advanced users/automation).

Outcome: Save hundreds of dollars per project while maintaining high perceived listener quality.

Table of contents

Creating a 10-hour audiobook using only premium AI voice tools can cost upwards of $300-$500. The “New AI Way” uses a hybrid strategy: paying for premium quality only where it counts (the first 30 seconds) and switching to a cost-effective model for the bulk of the content, saving ~90% on raw costs without the listener noticing.

Step 1: Segment Your Content

Divide your text into two distinct categories: Hooks and Body. The “Hook” is the first 1-2 minutes of the file or the start of a new chapter—this is where listener impressions are formed. The “Body” is everything else.

Open your script in a text editor.
Identify the Intro, Outro, and first paragraph of every chapter. Mark these for ElevenLabs.
Mark the remaining ~90% of the text for OpenAI.

Step 2: Generate Hooks with ElevenLabs

Use ElevenLabs for the sections that require maximum emotion and inflection to “sell” the quality to the listener.

Login to ElevenLabs.
Select a high-quality “Turbo” or “Multilingual” model.
Generate audio for your Intros, Outros, and Chapter headers.
Download these files as high-quality MP3s.

Step 3: Generate Body with OpenAI (The “Magic” Step)

This is where the cost savings happen. Once a listener is “anchored” to the voice in the intro, their brain becomes less critical of the slightly lower fidelity in the body content. OpenAI’s tts-1-hd model is significantly cheaper than ElevenLabs but sounds nearly identical once the ear adjusts.

Access the OpenAI API or a compatible playground.
Select the tts-1-hd model (it offers better dynamic range than standard tts-1).
Choose a voice (e.g., “Alloy” or “Echo”) that closely matches your ElevenLabs voice tone.
Generate the bulk of your text content.

Step 4: Normalize Audio Levels (Pick ONE Path)

Different AI engines output audio at different volumes (Loudness). If you just stitch them together, the volume drop will reveal the trick. Choose only one method below to match the files to -16 LUFS.

Method A: The “No-Code” Way (Easier)

Use Shutter Encoder for a drag-and-drop experience.

Open Shutter Encoder and drag your ElevenLabs and OpenAI files into the main window.
Select “Loudness & True Peak” from the “Choose function” list.
Set the Target Loudness to -16 LUFS (Standard for podcasts/mobile) and click “Start Function.”

— OR —

Method B: The “Pro” Way (Faster for Coders)

Use FFmpeg if you are comfortable with the terminal.

Run this command in your terminal for every file: ffmpeg -i input.mp3 -filter:a loudnorm=I=-16:TP=-1.5:LRA=11 -ar 48k output.mp3

Step 5: Merge and Finalize (Pick ONE Path)

Now that the files are the same volume, you need to glue them together into the final audiobook. Stick to the same tool you used in Step 4.

Method A: The “No-Code” Way (Shutter Encoder)

Clear the previous file list in Shutter Encoder.
Drag your newly normalized files in (ensure they are in the correct order).
Select “Merge” from the “Choose function” list and click “Start Function.”
Play the final file in any media player to ensure the transition is seamless.