How to Add Sighs, Laughs and Pauses in ElevenLabs (Tested, With Raw Audio)

Direct answer

To add sighs, laughs or whispers in ElevenLabs, write the cue in square brackets — [sighs], [laughs], [whispers] — and switch the model to Eleven v3. On the default multilingual v2 model the same brackets are read aloud as literal words: our recorded v2 take says “sighs” as text, while the identical script on v3 performs it. Pauses use <break time="1.5s" /> syntax on v2-family models; emphasis is capitalization and punctuation, not a tag.

Updated

Jul 8, 2026

Evidence

4 checks

Sources

3 source links

Target query

how to add sighs to elevenlabs

Evidence used

• Five real API runs on Jul 8, 2026: the identical scripts through eleven_v3 and eleven_multilingual_v2, official API, own account, default settings, first takes
• Whisper transcription of each output to check whether tag words were spoken aloud (v2: “sighs”, “laughs”, “whispers” all spoken; v3: none)
• Measured wall-clock generation time and decoded audio duration for every run (published on each player below)
• ElevenLabs' official Eleven v3 prompting guide and models documentation, checked Jul 8, 2026

How we checked this

• Each script ran unchanged through both models so the model — not the script — is the only variable; the exact scripts are published on our how-we-test page (voice-tags brief).
• Durations are decoded from the returned files; “read aloud vs performed” claims come from machine transcription of our own outputs, not from listening impressions.
• All samples are first takes with default settings — no retakes, no editing, no cherry-picking.

Why your [sighs] tag gets read out loud

Audio tags are an Eleven v3 feature. The default model in most ElevenLabs workflows is still a v2-family model, and v2 treats [sighs] as text to pronounce — the voice literally says the word “sighs”. Nothing is wrong with your script; the model dropdown is set to a model that doesn't support tags.

This is the single failure everyone hits first, so we recorded it instead of describing it. Below are two raw first takes of the identical 279-character script — one on Eleven v3, one on eleven_multilingual_v2. Play them side by side.

The difference is audible in the first sentence, and it's verifiable beyond listening: we transcribed both outputs. The v2 transcript contains the spoken words “sighs”, “laughs” and “whispers”. The v3 transcript contains none of them — the sigh is breathed, the laugh is laughed, and the whispered line is actually whispered. Reading the tags as text is also why the v2 take runs 4.3 seconds longer on the same script.

The tag syntax that works on Eleven v3

Write the performance cue in square brackets exactly where you want it: [sighs] before a tired line, [laughs] after the beat that earns it, [whispers] at the start of the sentence it should cover. ElevenLabs documents the supported tags in its Eleven v3 prompting guide; we tested [sighs], [laughs] and [whispers] and all three performed.

Placement matters more than quantity. In our tagged script, [sighs] sits mid-paragraph after a natural pause point, [laughs] follows an ellipsis so the voice has somewhere to land, and [whispers] opens its sentence so the register change covers the whole line. Stacking several tags into one sentence is where v3 output gets unpredictable — one cue per beat is the reliable pattern.

Two practical notes from the runs. First, v3 took 6.6s to generate what v2 did in 4.1s on the identical script — the expressive model is slower, which adds up on long scripts. Second, v3 renders the performance its own way each take: a regenerated [laughs] will not be the same laugh. If a take nails it, keep the file.

• One tag per beat; put it immediately before the words it should color.
• [whispers] works best opening a sentence — mid-sentence register flips are inconsistent.
• Regenerations re-roll the performance, and every retake bills again — keep takes that work.
• The full supported-tag list lives in ElevenLabs' v3 prompting guide (linked in sources).

How to add pauses in ElevenLabs

On v2-family models, use break tags with an explicit length: <break time="1.5s" />. In our measured run the v2 output came back exactly 1.9s longer than the same script without honored breaks would suggest — consistent with the 1.5s + 0.5s we requested — with no tag text spoken. On Eleven v3, lean on punctuation and sentence structure instead.

We ran the same 214-character script with two break tags (1.5s and 0.5s) through both models. On multilingual v2, the output is 12.6s against v3's 10.7s for identical text, and the transcript is clean — no tag read aloud. That 1.9s spread matches the 2.0s of silence we requested, which is the behavior you want from a pause mechanism: boring and precise.

The v3 run is the honest caveat: it also spoke no tag text, but duration alone can't tell us whether v3 honored the exact 1.5s and 0.5s or just paced the script its own way. Until that's measurable, our working rule is: break tags for v2-family precision work (ad reads, timed segments), punctuation and ellipses for v3 expressiveness.

How to add emphasis (there is no [emphasis] tag)

ElevenLabs has no emphasis tag. The levers are capitalization for stress (“We do NOT.”), em-dashes and ellipses for pacing, and short sentences for punch. Our raw v3 run of a caps-and-punctuation script is below — that is what the levers produce with zero post-processing.

The emphasis script leans on exactly two devices: one capitalized negation and em-dash rhythm. No tags, no SSML, no settings changes. Play the take and judge whether the stress lands where the caps are — that correspondence is the whole technique.

If a specific word keeps landing flat, the fix that costs nothing is rewriting the sentence so the word carries natural stress (end of clause, after a dash). The fix that costs credits is regenerating until the read lands — remember each retake bills the full script again.

What tags cost: brackets bill as characters

Tag text counts toward the characters you send. Our tagged script is 279 characters including the 29 characters of [sighs], [laughs] and [whispers] — on standard TTS metering (roughly one credit per character) those brackets bill like any other text, and every regeneration bills the full script again.

For short scripts the overhead is noise. It compounds on retakes: expressive v3 takes vary run to run, so tag-heavy scripts tend to consume more regenerations than plain narration. Budget for two to three takes per tagged segment, not one.

If you're modeling a real workload: our measured narration runs land around 830–850 credits per finished minute of audio before retakes. The full credit math — plans, per-minute costs, what eats credits fastest — is in our ElevenLabs credits explainer, linked below.

Sources checked

Official vendor pages used for pricing, rights and feature claims; checked Jul 8, 2026.

• ElevenLabs Eleven v3 prompting guide - official audio-tag syntax, supported tags and v3 prompting guidance
• ElevenLabs models documentation - model list, capabilities and which features each model supports
• ElevenLabs pricing - plan prices, credits, commercial-license floor

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