Feedback: speech-to-text-universal-streaming-turn-detection

Documentation Feedback

Original URL: https://assemblyai.com/docs/speech-to-text/universal-streaming/turn-detection
Category: speech-to-text
Generated: 05/08/2025, 4:22:49 pm

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Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:22:48 pm

Technical Documentation Analysis: Turn Detection

Overall Assessment

This documentation covers a complex technical feature but has several areas for improvement. While it provides good technical detail, it lacks practical guidance and clear user pathways.

Critical Issues

1. Missing Prerequisites & Setup Information

Problem: No information about how to enable or access this feature. Impact: Users can’t implement the feature without additional research.

Recommendations:

• Add a “Getting Started” section with:
  • API endpoint or WebSocket connection details
  • Required authentication/API keys
  • Basic setup code example
  • Prerequisites (streaming connection requirements)

2. Incomplete Code Examples

Problem: Only one minimal Python snippet for ForceEndpoint. Impact: Users struggle to implement the feature practically.

Recommendations: Add complete code examples for:

# Configuration example
config = {
    "end_of_turn_confidence_threshold": 0.8,
    "min_end_of_turn_silence_when_confident": 200,
    "max_turn_silence": 3000
}

# Event handling example
def handle_end_of_turn(event):
    print(f"Turn ended: {event['text']}")
    print(f"Detection method: {event['method']}")  # model-based or silence-based

3. Missing Response Format Documentation

Problem: No information about what events/responses users receive. Impact: Users don’t know how to handle turn detection events.

Recommendations: Document the response structure:

{
  "type": "EndOfTurn",
  "turn": {
    "text": "Hello, how are you today?",
    "words": [...],
    "confidence": 0.85,
    "detection_method": "model-based"
  }
}

Structure & Organization Issues

4. Improve Information Hierarchy

Current structure is confusing. Reorganize as:

# Turn Detection
## Quick Start
## How It Works
### Model-based Detection
### Silence-based Detection
## Configuration Options
## Code Examples
## Troubleshooting
## Advanced Usage

5. Add Decision Tree or Flowchart

The dual detection system is complex. Add a visual flowchart showing:

• When model-based detection triggers
• When silence-based detection takes over
• How they interact

Content Clarity Issues

6. Unclear Parameter Explanations

Problem: Technical parameters lack context about their impact.

Improve with practical guidance:

end_of_turn_confidence_threshold (0.0-1.0)
├─ 0.5-0.7: More responsive, may interrupt speakers
├─ 0.7-0.8: Balanced (recommended for most use cases)
└─ 0.8-1.0: More conservative, longer pauses before detection

Use cases:
• Customer service: 0.6-0.7 (quick responses)
• Interviews: 0.8+ (allow thinking time)

7. Missing Error Handling & Troubleshooting

Add sections for:

• Common configuration mistakes
• What happens when WebSocket disconnects
• How to debug turn detection issues
• Performance considerations

User Experience Improvements

8. Add Use Case Examples

Include specific scenarios:

## Common Use Cases

### Voice Assistant
- Recommended: `end_of_turn_confidence_threshold: 0.7`
- Rationale: Balance between responsiveness and accuracy

### Phone Interview Transcription
- Recommended: `end_of_turn_confidence_threshold: 0.9`
- Rationale: Allow for natural pauses and thinking time

9. Better Feature Comparison

Create a comparison table:

Feature	Model-based	Silence-based	Combined (Default)
Accuracy	High	Medium	Highest
Speed	Fast	Variable	Optimized
Best for	Natural conversation	Simple use cases	All scenarios

Missing Technical Information

10. Add Performance & Limitations

Document:

• Latency expectations
• Language support limitations
• Audio quality requirements
• Rate limits or usage constraints

11. Integration Guidance

Missing information about:

• How this works with other AssemblyAI features
• Webhook integration options
• Batch processing compatibility

Quick Wins

12. Immediate Improvements

1. Add a complete working example at the top
2. Create a parameter reference table with ranges and recommendations
3. Add FAQ section addressing common questions
4. Include debugging tips for when turn detection isn’t working as expected

13. Content Additions Needed

## FAQ
**Q: Why isn't turn detection triggering?**
A: Check that your confidence threshold isn't too high and ensure minimum speech duration is met.

**Q: Can I get callbacks for both detection methods?**
A: Yes, the response includes which method triggered the detection.

**Q: What languages are supported?**
A: [Add supported languages list]

This documentation has good technical depth but needs significant improvements in practical guidance, examples, and user experience to be truly effective for developers implementing this feature.

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