How ElevenLabs Explains Text to Speech and Synthetic Voice Creation
Overview
The ElevenLabs Blog explains that text to speech works in two stages: it first turns text into tokens and contextual vectors, then generates an acoustic representation that a vocoder renders as a waveform.
It uses the example of normalizing "$11" into "eleven dollars" before synthesis. The blog says prosody, the control of pitch and rhythm, makes neural TTS output sound human.
A second post from the same blog says synthetic voices are built with neural models trained on large datasets of real speech. To clone a voice, a user records themselves, and the model analyzes their phonetic patterns and inflection to replicate it, with accent, tone and pacing adjustable. The blog says these models replicate prosody and context rather than stitching together words or syllables.
Written by AI from the articles below · updated Nov 2, 6:08 PM ET
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Developments
2 developments
- Nov 2, 7:00 AM ET · 1 articleHow synthetic voices are created for natural-sounding speechElevenLabs Blog: How synthetic voices are created for natural-sounding speech
- Oct 26, 8:00 AM ET · 1 articleHow text to speech technology works, from text to natural voiceElevenLabs Blog: How text to speech technology works, from text to natural voice
Article timeline
The articles in this story. Times are ET.
- ElevenLabs BlogOfficialHow synthetic voices are created for natural-sounding speech
AISynthetic voices are made with neural AI models trained on large datasets of real human speech, which learn pronunciation, rhythm, and intonation. To clone a voice, a user records themselves, and the model analyzes their phonetic patterns and inflection to replicate it, with accent, tone, and pacing adjustable. Modern models sound natural because they replicate prosody and context rather than stitching together individual words or syllables.
- ElevenLabs BlogOfficialHow text to speech technology works, from text to natural voice
AIText to speech systems convert written words into audio in two stages, first turning text into tokens and contextual vectors, then generating an acoustic representation that is output as sound. Newer neural TTS engines use AI models to produce natural-sounding speech, with prosody handling the pitch and rhythm that make it sound human. The ElevenLabs Blog explains the pipeline using a worked example, from normalizing "$11" into "eleven dollars" to vocoder waveform generation.
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