Introducing Eleven v3 (alpha)

Try v3

7 tips for creating a professional-grade voice clone in ElevenLabs

Learn how to create professional-grade voice clones with ElevenLabs using these 7 essential tips.

Voice Clone Recording

Voice cloning has evolved from sci-fi curiosity to production staple. Whether you’re localizing a game, building a branded voice, or producing audiobooks at scale, a high-quality AI voice can streamline workflows and expand creative reach.

ElevenLabs Text to Speech technology makes it possible to achieve studio-grade results without a machine-learning background. But even the best model depends on disciplined inputs. 

1. Start with pristine recordings

In generative audio, "garbage in, garbage out" is doubly important. Poor training data limits audio quality, and flawed prompts lead to unsatisfactory results even with well-trained models. 

High-quality training data and precise prompts are essential for good generative audio outputs, as flawed input at either stage significantly compromises the final result.

Requirement Why it matters
Quiet, treated room (no HVAC, pets, traffic) Model learns background noise as part of the voice
Cardioid condenser or broadcast dynamic mic Off-axis rejection and low self-noise
44.1 kHz, 16-bit (or better) mono WAV Matches ingestion spec and preserves fidelity
Pop filter / windscreen Reduces plosives and low-end rumble
Flat EQ, no compression Preserves natural dynamics

Always record a short room tone first. If your DAW shows visible noise, fix it before reading a single line.

2. Capture expressive, varied speech

Original
Voice clone
Lily
Lily
Original
Lily
Lily
Clone
Chris
Chris
Original
Chris
Chris
Clone
Laura
Laura
Original
Laura
Laura
Clone
Create a replica of your voice that sounds just like you.

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 (0.3–0.5s) between lines 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) to give the Style slider something real to interpolate.

3. Clean your dataset

After recording:

  • Manually gate and de-click, or use tools like iZotope RX
  • 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.

Ryan Morrison Professional Voice Clone (PVC)

 / 

Ryan Morrison Instant Voice Clone (IVC)

 / 

Switching mic chains mid-recording confuses the model.

For multi-session projects:

  • Fix mic placement and gain
  • Record within the same 24–48 hour window to avoid vocal drift
  • If using old and new recordings, train separate voices and blend using Voice Mixing—don’t dilute a single clone

5. Feed the right amount of data

To achieve the desired balance between speed and quality in your voice clone, it's important to provide an appropriate amount of training data. The following table provides guidelines for data length, based on the intended application.

Use Case Minimum Sweet Spot Why
Quick demo / scratch track 2–3 min 5 min Fast iteration
YouTube / explainer videos 5 min 10–15 min Smooth cadence, good style range
Audiobooks / podcast host 10 min 20–30 min Natural inflection over hours
Multilingual brand or character 15 min 30–45 min per language Cross-language continuity

More than ~60 minutes can create diminishing returns. For nuanced needs, build sub-clones tuned to accent, emotion, or age.

6. Tune ElevenLabs settings

To achieve the best balance of speed and quality in your voice clone, it's important to provide the right amount of training data. The table below outlines recommended data lengths based on how you intend to use the voice.

Setting Effect Typical Range
Stability Lower = more variation; higher = consistent delivery 0.4–0.7 for narration; 0.2–0.4 for dialog
Similarity Boost Controls how strictly timbre matches training audio ≥ 0.75 for branded voices
Style Exaggeration Amplifies emotional cues in the dataset 0.1 for subtle; 0.3–0.5 for expressive
Accent / Latent Channels Advanced: blends multiple voices or traits Use for custom hybrid personas

Pro tip: Save a “Gold Preset” once tuned. Apply it in bulk for chapter reads or commercial spots.

7. Stress-test in real scenarios

Narration test: Paste a 500-word script with names, numbers, and dialogue. Listen for pacing or pronunciation issues.

Dialog test: Alternate clones in a chatbot or game engine. Evaluate timing and emotional contrast.

Multilingual test: For bilingual voices, run mixed-language lines. Assess smoothness in code-switching.

Play output at different LUFS targets to catch any mastering-stage artifacts. Maintain a feedback log—small dataset tweaks often outperform big setting changes.

Managing your voice clone library

Naming: Use [Project]_[Actor]_[Emotion]_[v1] Example: RPG_TavernKeeper_Jovial_v1

Version control: Clone before major edits to A/B compare changes.

Metadata: Record mic model, room setup, date, and rights-holder—essential for compliance.

Archival: Back up raw WAVs and training bundles (e.g., to S3 or LTO) in case of future re-training on new engine versions.

Real-world use cases

Voice cloning opens up a wide range of possibilities across different industries. Let's take a look at some specific examples of how this technology is being used and the benefits it provides

Industry Example Benefit
Audiobooks One narrator, localized into 6 languages Avoids rehiring multiple voice talents
Gaming NPCs change tone based on gameplay Infinite variation without new sessions
Advertising Always-on brand voice for promos No scheduling delays
Accessibility Consistent voice for video descriptions Increases user comfort and trust

Conclusion and next steps

A great voice clone is equal parts engineering and direction—clean input, thoughtful design, and precise tuning.

Ready to hear your own?

  1. Sign in to ElevenLabs Studio (free tier available)
  2. Upload 5–6 segments of 10 minute samples of high-quality audio
  3. Generate first outputs in seconds
  4. Refine with Stability and Style settings

Need more control? Upgrade for voice mixing, multilingual cloning, and longer content generation. Keep iterating. The voice you imagine is within reach.

Explore more

ElevenLabs

Create with the highest quality AI Audio

Get started free

Already have an account? Log in