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Voice Options

ADD CREATE uses high-fidelity neural voices for all audio narration. Voice selection happens during the Render step when you submit your script for synthesis.

Seven voices are available. You can preview any of them before committing to a render:

VoiceGenderCharacterBest For
AchernarFemaleProfessional, steady, clearNews-style narration, formal content
AoedeFemaleWarm, engaging, expressiveStorytelling, educational content
CharonMaleDeep, authoritative, calmSerious topics, in-depth analysis
FenrirMaleEnergetic, youthful, vibrantFast-paced or upbeat content
KoreFemaleBright, friendly, approachableCasual discussions, FAQs
PuckMalePlayful, light, conversationalDebate formats, informal pieces
ZephyrFemaleSmooth, sophisticated, calmExecutive summaries, corporate content

For dialogue formats (Deep Dive and Debate), two voices are used:

  • Voice A is the primary voice — used for the first speaker and for all narration in single-speaker formats.
  • Voice B is the second speaker in dialogue formats.

The default pairing is Achernar (Voice A) and Puck (Voice B). You can change either voice in the render settings.

Language
English (US)
Spanish
French
German
Japanese
Korean
Mandarin Chinese

When rendering, you can choose the file format for the audio output:

FormatDescription
WAVUncompressed — highest quality, larger file size
MP3Compressed — good balance of quality and size
OGGCompressed — well suited for streaming

You can also adjust the following when rendering:

  • Speed — how fast the voices speak. The default is normal speed; you can go slightly faster or slower.
  • Volume — raise or lower the output volume if needed.

Use these patterns to get more predictable results:

  • Keep inputs specific and scoped to one intent per generation request.
  • Save intermediate outputs often, especially before running major edits or regenerations.
  • Use review and assignment workflows early to reduce rework late in the lifecycle.

If results are not what you expected:

  • Verify source quality first (missing context, inconsistent structure, or conflicting inputs reduce output quality).
  • Re-check selected options and audience/profile settings before re-running.
  • If a job fails repeatedly, wait briefly and retry once; then escalate with the artifact or job context.

Different input context, settings, and model/runtime conditions can produce different outputs.

Regenerate when the core structure is wrong; manually edit when only wording, ordering, or style needs adjustment.

What is the best way to reduce iteration cycles?

Section titled “What is the best way to reduce iteration cycles?”

Start with clear scope, run smaller batches, and use review checkpoints after each major step.