Feedback: audio-intelligence-summarization

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/audio-intelligence/summarization
Category: audio-intelligence
Generated: 05/08/2025, 4:32:51 pm

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Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:32:50 pm

Technical Documentation Analysis: AssemblyAI Summarization

Overall Assessment

The documentation is well-structured with good code examples, but has several areas for improvement regarding clarity, completeness, and user experience.

Specific Issues & Recommendations

1. Missing Information

Critical Gaps:

• No expected response time information - Users need to know how long summarization takes
• Missing audio file requirements (formats, size limits, duration limits)
• No pricing/usage information - Users can’t assess cost impact
• Error handling examples are incomplete across all code samples
• No authentication setup instructions - just shows <YOUR_API_KEY>

Recommended additions:

## Prerequisites
- Valid AssemblyAI API key ([get one here](link))
- Audio file in supported format (MP3, WAV, M4A, etc.)
- Maximum file size: 5GB
- Recommended duration: 5 minutes to 2 hours for best results

## Processing Time
- Typical processing time: 15-25% of audio duration
- Example: 10-minute audio file = ~2-3 minutes processing time

2. Unclear Explanations

Issues:

• The dependency between summary_model and summary_type is mentioned but not clearly explained
• Language support section doesn’t explain why only English variants are supported
• The relationship between different summary types and their use cases needs better explanation

Improvements needed:

## Parameter Dependencies
When using custom summary formatting, both parameters are required:
- If you specify `summary_model`, you MUST also specify `summary_type`
- If you specify `summary_type`, you MUST also specify `summary_model`
- If you only set `summarization: true`, default values are used (informative + bullets)

3. Better Examples Needed

Current problems:

• Examples don’t show the actual API response structure
• No examples of different summary outputs side-by-side
• Missing error response examples
• Code examples don’t show real-world error handling

Recommended improvements:

## Summary Type Comparison
Using the same audio file, here's how different summary types compare:

**Original transcript excerpt:** "In today's meeting, we discussed three main topics..."

**bullets:**
- Discussed three main topics in today's meeting
- Decided to implement new project timeline

**headline:** "Team meeting covers three key topics and new timeline implementation"

**gist:** "Project meeting and timeline"

4. Structure Improvements

Issues:

• FAQ section is too brief and doesn’t address common user questions
• Summary models table is hard to scan - too much text in cells
• No troubleshooting section
• Missing “Next steps” or “Related features” section

Suggested restructure:

# Summarization

## Quick Start
[Minimal example]

## How It Works
[Brief explanation of the AI model]

## Configuration Options
### Summary Types
### Summary Models
### Language Support

## Complete Examples
[Full code samples with error handling]

## API Reference
[Current reference section]

## Troubleshooting
[Common issues and solutions]

## Related Features
- Auto Chapters
- Custom Summaries with LeMUR
- Speaker Diarization

5. User Pain Points

Authentication confusion:

• No guidance on where to get API key
• No example of setting up authentication properly

Parameter validation:

• Users won’t understand why their request fails if they only specify one of the required paired parameters
• No validation examples or error messages shown

Output expectations:

• Users don’t know what to expect in terms of summary quality or length
• No guidance on choosing the right summary type for their use case

Specific Actionable Fixes

1. Add a decision tree for summary types:

## Choosing Summary Type

**Need a quick overview?** → Use `headline` or `gist`
**Want key points highlighted?** → Use `bullets`
**Need comprehensive coverage?** → Use `bullets_verbose`
**Want readable paragraph format?** → Use `paragraph`

2. Improve the summary models table:

| Model | Best For | Output Style | Required Setup |
|-------|----------|--------------|----------------|
| `informative` | Lectures, presentations | Factual, structured | Single speaker content |
| `conversational` | Interviews, calls | Dialogue-aware | Multi-speaker content |
| `catchy` | Media titles | Engaging, brief | Short, punchy content |

3. Add comprehensive error handling:

try:
    transcript = aai.Transcriber().transcribe(audio_file, config)
    if transcript.status == 'error':
        print(f"Transcription failed: {transcript.error}")
    else:
        print(transcript.summary)
except Exception as e:
    print(f"Request failed: {e}")

4. Add output validation section:

## Validating Results
- Empty summaries may indicate audio quality issues
- Very short summaries might mean insufficient content
- Check transcript.status before accessing summary

5. Expand FAQ with practical questions:

• “Why is my summary empty?”
• “How do I choose between summary types?”
• “Can I summarize multiple languages?”
• “What if my audio is longer than 2 hours?”

These improvements would significantly enhance user experience and reduce support burden.

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