Your AI agents can now speak with genuine emotion. TaskAGI’s HyperVoice text-to-speech engine now supports inline emotion tags—simple markers you add directly to your text that control how each sentence sounds. No complex audio editing. No separate voice models. Just add a tag like [happy] or [angry] and your agent speaks with that emotional tone.
What this means: Customer service bots can sound genuinely apologetic when addressing complaints. Educational agents can sound excited when delivering good news. Marketing automation can hit the right emotional note for different message types. All from a single, simple workflow in TaskAGI.
How Inline Emotion Tags Work
The system is deliberately straightforward. Wrap any text segment in an emotion tag, and HyperVoice automatically generates that portion with the corresponding emotional expression:
| Emotion Tag | Vocal Tone | Best For |
|---|---|---|
| [happy] or [joy] | Cheerful, upbeat | Good news, confirmations, celebrations |
| [sad] | Melancholic, subdued | Empathy, apologies, serious concerns |
| [angry] | Intense, forceful | Urgent warnings, critical alerts |
| [fearful], [scared], [afraid] | Anxious, trembling | Risk warnings, cautionary messages |
| [surprised] | Astonished, exclamatory | Unexpected results, plot twists |
| [disgusted] | Repulsed, disapproving | Negative feedback, rejection messages |
| [neutral] | Normal, balanced | Standard information, default tone |
Text without emotion tags automatically uses the highest-quality voice model available, so you only apply emotion where it matters.
Real Example: Customer Service Response
[happy] Great news! Your order has shipped. [sad] Unfortunately, we're experiencing slight delays in delivery. [happy] But we're offering you 15% off your next purchase as an apology.
The agent delivers this message with three distinct emotional tones—enthusiasm about the shipment, genuine sympathy about the delay, and warmth about the compensation. The result feels human and appropriate, not robotic.
Why Emotional Expression Matters in AI Agents
Voice is how most people experience AI agents now. A monotone voice—even a high-quality one—feels cold and disconnected. Emotion makes interactions feel real.
Customer Service & Support
When a support bot apologizes for a problem, it should sound genuinely sorry. When it delivers good news, it should sound pleased. Customers respond better to emotionally-appropriate responses because they feel acknowledged, not just processed. This reduces frustration and increases trust in your automation.
Educational & Training Bots
An instructor explaining a difficult concept should sound patient and encouraging. A quiz bot should sound genuinely excited when you get the right answer. Emotional variation keeps learners engaged and makes content more memorable.
Marketing & Sales Automation
Different messages need different tones. A promotional message about a limited-time offer should sound urgent and excited. A follow-up message to a hesitant prospect should sound understanding and helpful. Emotion tags let you dial in the right tone for each message type without rebuilding workflows.
Accessibility & Inclusivity
Expressive speech is more accessible to users with cognitive differences or auditory processing challenges. Emotional tone provides additional context clues that help comprehension and engagement.
How to Use Emotion Tags in TaskAGI Workflows
Step 1: Add Tags to Your Text
In any node where you’re generating text for HyperVoice, simply wrap segments in emotion tags:
[happy] Welcome to our service! [neutral] Here's what you need to know. [surprised] We just added three new features!
Step 2: Connect to HyperVoice
Use TaskAGI’s HyperVoice text-to-speech node like normal. The emotion tags are automatically detected and processed—no additional configuration needed.
Step 3: Test and Refine
Play the generated audio in your workflow preview. Adjust emotion tags based on how the output sounds. You’ll quickly develop intuition for which emotions work best for different message types.
Practical Tips
- Don’t overuse emotion tags. A single emotional tone throughout a message is often more effective than switching emotions every sentence. Use tags strategically for emphasis.
- Match emotion to context. [angry] works for urgent alerts but sounds jarring in routine confirmations. Think about what emotion the user would naturally expect.
- Test with real users. Your interpretation of which emotion fits might differ from your audience’s. A/B test different emotional approaches.
- Combine with other voice settings. Emotion tags work alongside existing voice selection and speed controls. You can still customize voice type—emotion tags just add expression to whatever voice you choose.
- Use neutral for data-heavy content. When delivering numbers, timelines, or technical information, [neutral] often works better than other emotions. Save emotion for narrative or relational content.
Common Use Cases for Emotion Tags
E-commerce Order Updates
[happy] Your order is confirmed! [neutral] Tracking number: ABC123. [happy] It'll arrive by Friday!
Healthcare Appointment Reminders
[neutral] This is a reminder about your appointment. [happy] We're looking forward to seeing you on Tuesday at 2 PM.
Financial Alert Bot
[surprised] Your account balance has increased by $5,000. [happy] Your investment performance is up 12% this quarter!
Customer Support Escalation
[sad] I understand how frustrating this is. [angry] This should never have happened. [happy] Let me connect you with our manager who can resolve this immediately.
Educational Quiz Feedback
[happy] Correct! [surprised] You got it faster than most students. [neutral] Here's the next question.
Technical Details: How It Works Behind the Scenes
HyperVoice analyzes your text for emotion tags, segments the content, generates each portion with the appropriate emotional model, and seamlessly combines the audio into a single file. The process happens automatically—you don’t need to manage multiple audio files or worry about transitions.
Text without emotion tags continues to use the highest-quality voice model for best results, ensuring your agent sounds professional even when emotion variation isn’t needed.
Frequently Asked Questions
Can I use multiple emotion tags in one sentence?
Yes. The system processes tags sequentially, so [happy] Great news! [sad] But there's a catch. works perfectly. Each segment uses its designated emotion.
What if I use a tag that doesn’t exist?
Unknown tags are ignored, and that text uses the default high-quality voice model. This means you can safely experiment—invalid tags just fall back to neutral.
Does this work with all voice types?
Emotion tags work with HyperVoice’s supported voices. Some voice models may have more pronounced emotional variation than others. Test with your chosen voice to see how expressive the emotions sound.
Can I adjust emotion intensity?
Currently, emotion tags apply standard emotional expression. If you need fine-grained control over intensity, you can use multiple tags or adjust voice speed and pitch through other HyperVoice settings.
How do emotion tags affect audio file size?
Minimal impact. The system generates one continuous audio file regardless of how many emotion tags you use. File size is determined primarily by text length and voice model, not emotion variation.
Build More Human AI Agents
Emotion tags are a small feature with big impact. They let you build AI agents that sound thoughtful, appropriate, and genuinely engaged with your users—without complexity or extra work. Start experimenting with emotion tags in your next TaskAGI workflow and watch how users respond to voices that actually sound human.
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