Instructions vs. Inline Tags: Know the Difference
Qwen speech models can use more than one kind of delivery control, including natural-language instructions and model-specific inline performance syntax. They solve different problems and are not interchangeable. Check the documentation for the exact model selected in your workflow before using either control.
| Control | Where it goes | Scope | Best for | Model support |
|---|---|---|---|---|
| Natural-language instructions | Model-specific instruction field | Whole request | Speaker identity, baseline timbre, pace, and style | Compatible Qwen3-TTS models documented with instruction control |
| Inline delivery syntax | Inside the text field | Model-specific | Delivery changes within a script | Only models that explicitly document the syntax |
| Vocal-event syntax | Inside the text field | Model-specific | Laughter, sighs, gasps, and similar events | Only models that explicitly document the syntax |
The simplest mental model is:
Instructions define the speaker. Tags direct the performance.
Do not assume every Qwen speech model supports both. If an instruction has no effect or a tag is spoken aloud, confirm the selected model before rewriting the prompt.
How to Write Effective Qwen3 TTS Voice Instructions
Voice instructions describe the sound you want in natural language. Instead of tuning pitch curves or prosody parameters, you describe perceptible qualities such as age, pitch, speaking rate, emotional baseline, and vocal texture.
Three practical constraints matter:
- Use a Qwen3-TTS model that officially documents instruction control when you need it.
- Write instructions in English or Chinese and avoid mixing unrelated languages.
- Check the current model documentation for its input limit before using a long instruction.
The limit is generous, but shorter prompts are usually easier to control. A focused description of 30–80 words gives the model enough detail without introducing contradictions.
Here is an illustrative request:
response = client.audio.speech.create(
model="qwen3-tts-instruct-flash",
instructions=(
"A composed middle-aged man with a deep, resonant timbre. "
"Speak slowly and clearly for documentary narration."
),
text="This forest has been growing here for three thousand years.",
)
Treat the example as a prompt pattern; use the exact request fields required by your SDK or deployment.
Where voice instructions work well
- Audiobooks and audio drama: keep a narrator or character voice consistent across many scenes.
- Advertising: test the same script with several personas before choosing a final direction.
- Games and animation: create recognizable voices for NPCs and recurring characters.
- Voice assistants: encode a stable brand personality into the baseline delivery.
- Documentary and news narration: specify steady pacing, clear diction, and restrained emotion.
Five Principles for Better Voice Descriptions
1. Be specific, not vague
Words such as “nice,” “normal,” or “professional” leave too much room for interpretation. Describe audible properties instead:
- Weak:
A nice professional voice. - Better:
A composed woman with a mid-low pitch, crisp diction, and a steady medium pace.
2. Use several dimensions
Female voice describes only one dimension. Add age, pitch, pace, emotion, texture, and purpose to reduce variation between generations.
3. Prefer objective sound qualities
Write what a listener could hear. Higher pitch with energetic sentence endings is more actionable than a voice everyone will love.
4. Describe qualities instead of imitating a person
Avoid asking for a celebrity, actor, presenter, or other identifiable person. Describe the acoustic qualities you want: warm, gravelly, bright, restrained, theatrical, or conversational.
5. Remove redundant adjectives
Stacking near-synonyms does not multiply an effect. Gentle, soft, tender, mellow, soothing spends many words on one dimension while leaving pace, pitch, and purpose undefined.
The Seven-Dimension Voice Prompt Framework
When you are unsure what to write, build the instruction from seven dimensions.
| Dimension | Useful vocabulary |
|---|---|
| Gender | male, female, neutral |
| Age | child, teen, young adult, middle-aged, senior |
| Pitch | high, mid, low, slightly high, slightly low |
| Rate | fast, medium, slow, slightly fast, slightly slow |
| Emotion | cheerful, composed, gentle, serious, lively, calm |
| Character | magnetic, crisp, raspy, rounded, sweet, full-bodied |
| Purpose | news, advertising, audiobook, game character, assistant, documentary |
Use this reusable formula:
Age + gender + pitch or timbre + speaking rate + emotional baseline + purpose
Copy-and-paste voice instruction templates
Audiobook narrator
Middle-aged male, around 40, with a mid-low pitch and a warm,
slightly magnetic timbre. Use a slow, steady pace and restrained
emotion for long-form novel narration.
E-commerce product video
Young woman, around 25, with a higher pitch and crisp, cutting-through
timbre. Speak slightly fast with warm, persuasive energy and gently
rising sentence endings.
Premium brand film
Middle-aged woman with a rounded low timbre. Use a slow pace,
generous pauses, and a restrained but assured delivery for a
high-end brand film.
Game antagonist
Middle-aged man with a low pitch and raspy, gravelly timbre.
Speak slowly with a cold, menacing emotional baseline for a
game antagonist.
Everyday voice assistant
Young adult with a neutral-leaning female voice, mid pitch, and a
clean, clear timbre. Use a medium pace that feels friendly, natural,
and unforced for everyday questions and answers.
Science documentary
Male, age 35 to 45, with a mid-low pitch and precise articulation.
Use a medium-slow pace, rational tone, and a subtle sense of
curiosity for science documentary narration.
Emotion Tags and Rich-Language Tags
Some Qwen Audio TTS models document inline syntax placed directly in the text. The exact supported syntax and scope are model-specific, so use the current official documentation before relying on it in production.
Emotion and delivery tags: span scope
A control tag affects the words that follow it until another control tag appears or the text is segmented.
| Tag | Effect | Tag | Effect |
|---|---|---|---|
[sad] | Sad | [bored] | Bored |
[amazed] | Amazed | [tired] | Tired |
[angry] | Angry | [excited] | Excited |
[serious] | Serious | [curious] | Curious |
[shouting] | Shouting | [whispers] | Whispering |
[asmr] | Soft ASMR delivery | [panicked] | Panicked |
[sarcastic] | Sarcastic | [empathetic] | Empathetic |
[mischievously] | Mischievous | [reluctantly] | Reluctant |
[crying] | Crying delivery | [trembling] | Trembling |
[very slowly] | Very slow speech | [very fast] | Very fast speech |
[scornful] | Scornful | [like dracula] | Deep, eerie style |
[deep and loud shouting] | Deep, loud shouting |
Example:
[serious]Please pay attention to the safety instructions.
[excited]All right, let's begin!
The second tag replaces the first emotional direction for the text that follows.
Rich-language tags: point scope
Rich-language tags insert a vocal event at one position without changing the surrounding emotional baseline.
| Tag | Vocal event |
|---|---|
[gasp] | Sharp intake of breath |
[sighing] | Sigh |
[clears throat] | Throat clearing |
[giggles] | Giggle |
[laughing] | Laughter |
[cough] | Cough |
[snorts] | Snort or scoff |
You can place a point event inside a tagged emotional span:
[excited]The weather is fantastic today!
[laughing]Let's go out together!
[excited] controls the ongoing delivery. [laughing] inserts laughter at that point, after which the excited delivery continues.
Radio-drama example
[tired][sighing]Another day of working until midnight.
[curious]Hm—who left this letter on my desk?
[gasp][panicked]This... this cannot be happening!
Use punctuation as part of the direction. Dashes, ellipses, commas, and sentence boundaries help the model infer timing without adding a tag to every phrase.
Can You Combine Instructions and Tags?
Think of instructions and tags as complementary concepts, but check model support before trying to use them in one request.
- A compatible Qwen3-TTS model can use natural-language instruction control for speaker-level direction.
- A Qwen Audio TTS model may use documented inline syntax for performance control.
Based on those support boundaries, do not assume a single model accepts both mechanisms. Choose the control system that matches your task:
- Need a stable, custom speaker persona? Use instruction control.
- Need emotion changes and vocal events inside a script? Use a tag-capable Qwen Audio TTS model.
For a larger production, keep a reusable persona brief alongside the script even when the selected model only accepts tags. That brief remains useful for casting a base voice, reviewing consistency, and moving the project between compatible models.
Three rules for natural tagged speech
- Do not over-tag. One control tag per sentence or emotional beat is usually enough.
- Place point events logically. A sigh normally belongs before or after a thought, not in the middle of an unrelated phrase.
- Restate the mood in long scripts. Because control tags persist, repeat the intended tag at paragraph boundaries when consistency matters.
Troubleshooting Qwen TTS Prompts
| Symptom | Likely cause | Fix |
|---|---|---|
| Instructions have no effect | The selected model does not support instruction control or uses a different field | Check the model documentation and the current interface |
| Tags are spoken aloud | The selected model does not support that inline syntax | Remove the syntax and check the model documentation |
| Voice changes between runs | The voice description leaves too many dimensions undefined | Add age, pitch, pace, timbre, and purpose |
| Emotion sounds flat | The script has no supported performance direction | Add a control tag before the relevant sentence |
| Style shifts unexpectedly | Tag scope or automatic segmentation was misunderstood | Restate the control tag at each paragraph |
| Instruction is rejected or truncated | The prompt exceeds the model limit | Shorten it and remove stacked synonyms |
| Speech sounds unnatural | Too many tags interrupt the prosody | Keep tags at sentence or scene boundaries |
| The output feels contradictory | Prompt dimensions fight each other | Remove conflicts such as “calm” plus “frantic” |
A Repeatable Prompt-Tuning Workflow
- Write a baseline voice instruction. Use the seven-dimension formula and keep it under roughly 40 words for the first test.
- Use one fixed test passage. Include a statement, a question, a number, and a longer sentence so you can compare pacing and articulation.
- Generate several samples. Listen for changes in timbre, pace, and emotional baseline.
- Change one dimension at a time. Replace
medium pacewithslightly slowwithout rewriting everything else. - Choose the correct model for performance control. If the script needs mid-scene emotion changes, move to a tag-capable model.
- Add tags only at key beats. Start with one tag per sentence, then remove any tag that does not improve the result.
- Save the validated pattern. Store the final persona brief, model name, test script, and tag conventions as a reusable project template.
A compact test passage
Welcome to the demonstration. Today we will review three practical ideas.
Why do they matter? Because a clear voice makes complex information easier
to understand. Take a short pause, then finish with calm confidence.
This passage exposes pace, question intonation, number pronunciation, transitions, and the ending tone in a small amount of text.
Frequently Asked Questions
What makes a good Qwen3 TTS prompt?
A good prompt describes audible qualities across several dimensions: age, gender, pitch, rate, emotional baseline, vocal texture, and purpose. It stays concise and avoids contradictory adjectives.
How long should a voice instruction be?
Use the current model documentation for input limits. A focused 30–80-word instruction is usually easier to tune. Start shorter and add only the dimensions the output is missing.
Why is Qwen TTS reading my emotion tags aloud?
The selected model may not support that inline syntax. Remove the syntax, then confirm the current model documentation and interface before trying a documented alternative.
Should I add an emotion tag before every sentence?
No. Add a new control tag only when the intended delivery changes or when a long passage needs the mood restated. Excessive tags can make prosody sound fragmented.
Can I ask Qwen3 TTS to sound like a celebrity?
Describe vocal qualities rather than requesting imitation of an identifiable person. This produces a clearer prompt and avoids unnecessary personality-rights and copyright concerns.
Final Prompt Checklist
Before generating, confirm that:
- The selected model supports the control mechanism you are using.
- The voice instruction describes several audible dimensions.
- Every adjective contributes new information.
- No two directions contradict each other.
- Emotion tags appear before the text they should control.
- Vocal-event tags sit at natural moments in the sentence.
- Long scripts restate important control tags at paragraph boundaries.
- You changed only one variable since the previous test.
Qwen speech prompting is less about writing a dramatic paragraph and more about giving the model a clean production brief. Define the stable voice with specific, objective language; direct changing emotions only where the model supports inline tags; and tune one dimension at a time. That process is faster, more repeatable, and far easier to scale across a full project.
Method note
How We Tested
This guide is based on official model documentation and the current qwen3tts.net implementation. It does not represent an independent benchmark unless explicitly stated.
Read the full methodologySources & evidence
Model documentation used for this guide
- Qwen3-TTS official model repository
Official model documentation · QwenLM
- Qwen Audio 3.0 TTS documentation
Official model documentation · Qwen Audio
Put the guide into practice
Test Your Qwen3 TTS Prompt
Start with one of the voice instruction templates, generate a short sample, and adjust one dimension at a time until the delivery fits your project.
Open Text to Speech