Documentation
API Reference
Documentation
API Reference
Book a meeting
Linkedin
Github
  1. Guides
  • Introduction
  • Get started
    • Quickstart
    • Authentication
  • Core concepts
    • Agents
    • Phone numbers
    • Calls
    • Webhooks
  • Webhooks
    • Overview
    • Assistant request
    • Tool calls
    • Status update
    • End of call report
    • Security
  • Guides
    • Campaigns
    • xAI Realtime Integration
    • Voice selection psychology
    • Analysis templates
    • BYOK Setup
    • Call analysis
    • Call Transfers
    • Custom Tools
    • Sip Trunks
    • Tool templates
    • Voicemail detection
    • Autonomous silence detection
    • Billing
    • Error codes
    • Rate limits
    • Troubleshooting
  • Api's
    • Campaigns
    • Agents
    • Voices
    • BYOK
    • Analysis templates
    • Tool templates
    • Organization
    • Phone numbers
    • Sip trunks
    • Calls
    • Call control
    • Usage
    • Domains
Documentation
API Reference
Documentation
API Reference
Book a meeting
Linkedin
Github
  1. Guides

Voice selection psychology

Voice Selection: The Psychology of AI Phone Agents#

When deploying AI phone agents, voice selection is often underestimated. Many assume that the most human-like, natural-sounding voice is always the best choice. However, real-world deployments reveal a more nuanced picture.

The Uncanny Valley of Voice AI#

When callers know they're speaking with an AI (as required by transparency regulations), but the voice sounds indistinguishable from a human, a psychological tension emerges. This creates what we call the "Uncanny Valley of Conversation":
Callers feel uncomfortable being direct with something that sounds human
They hesitate to give short, efficient answers like "Yes" or "No"
Social norms around politeness and small talk feel awkward to ignore
The mismatch between knowing it's AI and hearing a human voice causes cognitive friction

The Case for Robotic Voices#

Our experience implementing hundreds of AI agents in production environments has revealed a counterintuitive finding: slightly robotic voices often outperform natural voices in specific use cases.

Why Robotic Voices Work#

1.
Permission to be Direct
When a voice clearly signals "I am a machine," callers feel comfortable responding efficiently. They don't feel rude saying "No" without explanation or answering questions without pleasantries.
2.
Reduced Social Pressure
Human-sounding voices trigger social scripts. Callers feel obligated to be polite, make small talk, or soften rejections. A robotic voice removes this pressure.
3.
Clearer Expectations
Callers immediately understand the interaction paradigm. They know to speak clearly, answer directly, and that the system won't be offended by brevity.
4.
Faster Interactions
Without the social overhead of human-like conversation, calls complete more quickly. Both parties get to the point faster.
5.
Higher Completion Rates
In many deployments, we've observed that callers are more likely to complete interactions with robotic voices because the interaction feels less awkward.

When to Use Each Voice Type#

Use Robotic/Local Voices For:#

Use CaseWhy It Works
Appointment ConfirmationsCallers just need to say "Yes" or reschedule
Payment RemindersDirect, transactional interactions
Survey CollectionClear questions, simple answers
Status UpdatesInformation delivery, minimal back-and-forth
Verification Calls"Please confirm your date of birth"
Queue Callbacks"Your table is ready" or "A representative is available"
Inbound Support TriageRouting calls to the right department

Use Human-Like Voices For:#

Use CaseWhy It Works
Sales CallsBuilding rapport and trust matters
Complex SupportEmpathy and patience feel important
Sensitive TopicsHealthcare, financial hardship, complaints
Relationship BuildingWhen the call itself is part of the brand experience
High-Value CustomersPremium experience expectations
Persuasion RequiredNegotiations, upsells, retention

The Technical Trade-Off#

Beyond psychology, there's a practical consideration:
AspectRobotic/Local VoiceHuman-Like Voice
LatencyVery low (~50ms)Higher (~200-500ms)
CostMinimalPer-character billing
ReliabilityNo API dependenciesExternal service required
LanguagesLimited selectionWide variety
CustomizationFixed voicesVoice cloning available

Our Recommendation#

Start with robotic voices for transactional use cases. You may be surprised by the results. Many teams default to expensive, natural-sounding voices assuming they're better, only to find that when they try a robotic voice:
Callers respond faster
Completion rates are higher
Costs are significantly lower
Latency is reduced
Then A/B test with natural voices for use cases where relationship-building matters.

The Optimal Configuration#

For most AI phone agents, we recommend:
ComponentRecommendationWhy
STT (Speech-to-Text)Premium provider (Deepgram, etc.)Accurate understanding is critical
LLM (Language Model)Powerful model (GPT-4, Claude, etc.)Reasoning, instruction-following, function calling
TTS (Text-to-Speech)Consider local/roboticOften improves user experience
The intelligence should be in understanding and reasoning. The voice is just the delivery mechanism, and a clearly artificial voice can actually improve the interaction.

Summary#

Don't assume human-like is always better. Match your voice selection to your use case:
Transactional, efficient interactions → Robotic voice
Relationship-building, emotional interactions → Human-like voice
Test both. Measure completion rates, call duration, and user satisfaction. The results may surprise you.
Modified at 2026-01-15 15:33:41
Previous
xAI Realtime Integration
Next
Analysis templates
Built with