Generating Audio

Audio Generation

Turn a script into spoken audio via the audio_generate tool. Two decisions drive quality: which voice reads it, and how the script is written for the ear.

Scope. Speech — a voice reading written words, delivered as its own audio file. Nothing here makes non-speech sound, alters audio that already exists, or combines two tracks into one.

Lip-synced dialogue spoken by a character inside a video clip belongs to generating-videos.

Workflow

Step 1: Settle the script

Generate only from the exact words that will be spoken.

• Supplied → use them verbatim.
• Enough to write them — the product, audience, platform, and length are known → draft the script and show it before generating.
• Not enough → ask. Never invent a tagline, product claim, or brand name to fill the gap.

Write to a duration. Speech runs about two to three words a second, so a fifteen-second read is thirty to forty-five words. Set the word count before writing, and trim words rather than speeding up the delivery.

Step 2: Pick the model

eleven-v3 is the default — the most expressive read, and right for anything heard as a performance. Reach for another only on a clear signal:

When the user names a model, use it. Per-request character limits differ sharply between models, and an over-limit script is rejected rather than truncated — list_audio_models carries each ceiling.

Step 3: Pick the voice

Call list_voices, filtered by what the brief demands — gender, accent, age, use_case, language, or free-text search. Each row carries a preview_url. There is no default voice: every request needs a voice_id chosen here, passed as voice. Display names are not accepted.

• A stated gender, accent, or age is a hard filter — apply it, don't trade it away on tone. Read the attribute back from the row's own fields; never infer it from the voice's name.
• Let the user hear the options. Unless they named a voice, offer two or three candidates with their preview_urls and let them pick.
• Choose on tone: what is the listener doing (half-watching a social clip wants attack and momentum; following an explainer wants a voice that stays out of the way), and whose voice is it meant to be (a brand narrator should stay neutral enough to reuse; a character should match the age and register of the writing).
• Non-English script → check the row's language, and that the model of Step 2 covers it.
• A voice_id the user pastes themselves is taken as given.
• Reuse the chosen voice_id for every clip in the job.
• Nothing matched → a normal result, not a dead end. Drop the narrowest facet — use_case first, then age — and search again. Only when gender and accent alone come back empty is the account genuinely short of voices; then relay the tool's hint verbatim, since the cause and the fix differ by provider and by whose key is in use.

Step 4: Prepare the text

text is read out word for word, so write it the way it should sound.

• Strip anything unspoken — stage directions, speaker labels, bracketed cues, markdown.
• Spell out numbers, dates, currency, acronyms, and URLs as a person would say them.
• Punctuate for pacing — commas and full stops become pauses, and are the main lever on rhythm.

Direct the delivery with stability and style (references/directing-the-read.md), never with instructions written into the text.

Step 5: Generate

Speech comes only from audio_generate. If it errors, or no voice fits, say so and stop — never substitute another text-to-speech tool the host happens to expose. A different engine means a different voice, no access to the account's voices, and output outside the media directory.

Call audio_generate with a requests list — one object per clip, up to ten per call.

• Per object: text and voice (both required — the voice_id from Step 3); model only when Step 2 chose a non-default; speed, stability, style, similarity_boost, format as needed.
• Split only where the audio will actually be cut — per scene, or per section placed separately. Objects generate independently, so a continuous read split across two of them seams audibly.
• Hold one voice and model across every object, for the same reason. In a dialogue, one voice per character, consistent across that character's lines.
• Repeat a line to get alternate takes — different voices when the choice is unclear, or the same voice twice at low stability. Worth it on one short line, not a whole script.

Step 6: Return

Share the audio file path(s). When the script was split, label each with the section it covers.

Edge cases

• Something other than speech is asked for (music, sound effects, ambience, re-voicing, dubbing, cloning a voice from a sample) → say so plainly rather than substituting something else. In particular, do not generate a clip through generating-videos to get music or effects out of its native audio: that bakes the sound into the picture, so it can never serve as a track the user mixes. An already-cloned voice still works by its voice_id, and another language works by translating the script and generating it fresh.
• Tracks need mixing or timing ("the voiceover under the music", "a swoosh on the logo") → deliver clean speech and let the user assemble it in their editor.
• Part of the brief is speech and part isn't → state the limits in one message up front, then deliver the speech. Never generate first and disclose the gaps after.
• Script over the model's character limit → split it at a natural break, or switch to a higher-ceiling model.
• error: "no_voices_available" → relay the hint; it distinguishes an empty account from a key lacking permission to read voices, and the fixes differ.
• Part of a batch fails → keep the takes that worked and resend only the failed lines.
• The read itself came out wrong (flat, erratic, mispronounced, stress on the wrong word) → references/directing-the-read.md diagnoses it symptom by symptom.
• Safety rejection → remove the sensitive wording and retry once.
• Generic failure → retry once as-is, then report the error.
• error: "no_provider_configured" → relay the tool's hint (the user must set their key).

Reference

• references/directing-the-read.md — tuning the delivery with stability, style, similarity_boost and speed, and diagnosing a read that isn't working.