ElevenLabs has the capability to replicate the nuanced details of human speech, including emotion, pacing, and prosody, but the quality of this reproduction is directly dependent on the presence and variation of these elements within the audio data used to train the model.
In other words, the AI can only effectively recreate what it has been shown during the training process. If the dataset lacks expressive variations or contains flat, monotonous speech, the resulting voice clone will likely reflect those same qualities.
Include:
- Neutral narrative
- Dialog with changing energy
- Smiles, whispers, and emphasis
Insert short silences (1–1.5s) between paragraphs and shorter between sentences to teach natural pause behavior. Avoid vocal fry or throat clearing unless you want it replicated.
For character work, record multiple “mood passes” (e.g., calm, excited, distressed).
3. Clean your dataset
After recording:
- Remove repeated takes, stutters, filler words, and disruptive breaths
- Normalize to –3 dBFS, but avoid compression
The goal: a dataset that already sounds ready for release. That quality will propagate to every output.
4. Maintain consistent conditions
When I recorded my first Professional Voice Clone I gave it a number of sound files recorded in different locations, thinking voice is voice. For the final version I recorded it all in my home office, reading from the same script. It still wasn't perfect but it is much better than the instant voice clone.