The most realistic AI voice generator available. Used by podcasters, authors, content creators, businesses, and accessibility advocates worldwide. Clone voices, narrate anything, create audio content at scale. History, how to use it, 15 prompts, and technical depth. Official sources only.
ElevenLabs is an AI that converts text to speech — but at a quality level that was not possible before AI. You paste in text, choose a voice (from their library of hundreds, or a clone of your own voice), and ElevenLabs generates audio that sounds like a real human reading it. Not a robot voice. Not an automated phone system. A warm, natural, expressive human voice.
Available free (with limits) at elevenlabs.io.
Real uses that changed things for people
An author with dyslexia used ElevenLabs to listen back to her own writing in her own cloned voice — helping her catch errors she couldn’t spot visually.
A small business owner in Manchester used ElevenLabs to create professional-sounding phone hold messages and website audio content for £10/month — work that would have cost hundreds from a voice actor.
A teacher created audio versions of lesson materials so students with reading difficulties could access the content equally.
Who made ElevenLabs?
ElevenLabs was founded in 2022 by Mati Staniszewski and Piotr Dabkowski — two Polish engineers who previously worked at Google and Palantir respectively. The company is headquartered in New York. By 2024, ElevenLabs had raised over $80 million and was valued at over $1 billion — the fastest AI startup to reach unicorn status at the time.
The company’s mission, as stated in their documentation: to make content universally accessible through voice — in any language, for anyone.
The history of ElevenLabs
2022: Founded on a specific frustration
Mati Staniszewski’s founding story: he wanted to watch Hollywood films dubbed into Polish — but the dubbing quality was always jarring, never matching the emotion and nuance of the original performance. He and Piotr Dabkowski believed AI could produce voice synthesis good enough to solve this — and built ElevenLabs to prove it.
January 2023: Launch and immediate attention
ElevenLabs launched in January 2023. Within weeks it went viral — users discovered that the voice cloning capability was remarkably convincing. A sample of just a few minutes of someone’s voice was enough to clone it with high fidelity. This attracted both excitement (accessibility, content creation, dubbing) and concern (potential for fraud and misinformation).
The misuse challenge — and the response
In early 2023, ElevenLabs faced significant criticism when users generated fake audio of celebrities and public figures saying things they never said. The company responded by implementing stricter identity verification for voice cloning, a content policy prohibiting certain uses, and a voice authentication system to detect ElevenLabs-generated audio.
2023–2024: Expanding capabilities
ElevenLabs expanded rapidly: multilingual voice synthesis covering 29+ languages, a voice library with hundreds of professionally recorded voices, the Projects feature for long-form audio book creation, and Dubbing — the ability to translate and dub video content into other languages while preserving the original speaker’s voice characteristics.
2025–2026: The professional standard
ElevenLabs became the dominant provider for professional AI voice work. Major publishers, game studios, e-learning platforms, and content creators adopted it. The API became widely used for building voice-enabled applications.
What ElevenLabs can do
Text to speech — Convert any text to natural-sounding audio in 29+ languages
Voice cloning — Clone your own voice (or with permission, any voice) from a short sample
Audiobook creation — Narrate entire books with consistent voice quality
Podcast production — Generate narration, intros, outros
Video dubbing — Translate video audio to other languages preserving voice characteristics
Accessibility — Create audio versions of text content for visually impaired users
Business voice content — IVR systems, hold messages, explainer videos
Game and app audio — Character voices and dynamic narration
Free vs paid
Free
10,000 characters/month. Access to voice library. 1 custom voice.
Starter — $6/mo
30,000 characters. 10 custom voices. Commercial use licence.
Creator — $22/mo
100,000 characters. 30 voices. Projects and dubbing features.
ElevenLabs’ quality is so good that the main skill is choosing and configuring the right voice, and writing text that sounds natural when spoken aloud (conversational language, not written language).
Writing for voice — the key difference
Written language and spoken language are different. For best results: use contractions (it’s, we’re, don’t), avoid very long sentences, use commas to control pacing, write numbers as words (“twenty-three” not “23”), and avoid abbreviations (spell them out). Read your text aloud before generating — if it sounds awkward spoken, it will sound awkward generated.
1. Professional explainer narration
[Write your script here — remember to use conversational language, contractions, and natural sentence rhythms. Break long explanations into shorter sentences. Use pauses indicated by commas. Read it aloud to yourself first.]
2. Podcast intro script
Welcome to [podcast name]. I’m [host name], and today we’re going to be talking about [topic]. If you’ve ever wondered [question that sets up the episode], then this episode is for you. Let’s get into it.
3. E-learning module narration
In this section, we’re going to look at [topic]. By the end, you’ll understand [specific outcome]. Let’s start with the basics. [Continue with conversational explanation — avoid bullet points and formal lists in the script]
4. Voicing text in multiple languages (Dubbing)
[Upload your video to ElevenLabs Dubbing. Select source and target language. Choose whether to use the original speaker’s cloned voice or a library voice. ElevenLabs translates and re-voices the entire video, matching lip movements where possible.]
5. Business phone system message
Thank you for calling [business name]. Our team is currently helping other customers. We’ll be with you shortly. If you know your party’s extension, you can dial it at any time. Otherwise, please stay on the line and we’ll answer your call as soon as we can.
ElevenLabs API
from elevenlabs import ElevenLabs
client = ElevenLabs(api_key="your-api-key")
audio = client.text_to_speech.convert(
voice_id="21m00Tcm4TlvDq8ikWAM", # Rachel voice
text="Hello, this is a test of ElevenLabs.",
model_id="eleven_multilingual_v2",
output_format="mp3_44100_128"
)
with open("output.mp3", "wb") as f:
for chunk in audio:
f.write(chunk)
ElevenLabs uses a neural text-to-speech (TTS) architecture based on diffusion models operating in the audio domain. Unlike earlier concatenative TTS systems (which spliced recorded phonemes) or parametric systems (which modelled vocal tract physics), neural TTS models learn directly from large datasets of human speech, capturing prosody, emotion, and speaker characteristics in their weights.
The voice cloning capability is achieved through speaker embeddings — a learned vector representation of a speaker’s voice characteristics that is extracted from a short reference sample and used to condition the generation model. ElevenLabs’ Instant Voice Cloning requires approximately one minute of clean audio; Professional Voice Cloning achieves higher quality with 30+ minutes of high-quality recordings.
Official documentation
ElevenLabs does not publish technical papers about their model architecture. The most detailed public technical information is available in their API documentation and model descriptions: elevenlabs.io/docs/overview/models
Multilingual models
ElevenLabs’ multilingual v2 model supports 29 languages with a single model that maintains voice consistency across languages — allowing a cloned voice to speak in French with the same speaker characteristics as the English original. This cross-lingual voice preservation is achieved through language-independent speaker embeddings separated from language-specific phoneme representations in the model architecture.