Feedback: getting-started-transcribe-an-audio-file

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/getting-started/transcribe-an-audio-file
Category: getting-started
Generated: 05/08/2025, 4:30:30 pm

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Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:30:29 pm

Technical Documentation Analysis: AssemblyAI Transcription Tutorial

Overall Assessment

This documentation provides a solid foundation for getting started with audio transcription, but has several areas for improvement in clarity, completeness, and user experience.

Specific Feedback by Category

1. Missing Information

Critical Missing Elements:

• Expected execution time: Users need to know transcription can take 15-30% of audio duration
• File size limits: No mention of maximum file size or duration limits
• Rate limiting: Missing information about API rate limits
• Cost information: No mention of pricing or free tier limits
• Supported audio formats: References FAQ but should list common formats directly
• Error troubleshooting: Limited error handling examples

Required Prerequisites:

## Prerequisites
- API key from AssemblyAI (free tier includes X minutes)
- Audio file ≤ X MB or X hours duration
- For local files: Supported formats (MP3, WAV, M4A, etc.)
- Internet connection for API access

2. Unclear Explanations

Confusing Concepts:

• Speech model selection: The explanation of “prompt-based speech model” and “cost-performance tradeoffs” lacks context
• Polling mechanism: Why polling is necessary isn’t explained
• Upload URL lifecycle: The 24-hour deletion policy is buried in a note

Suggested Improvements:

## Why Polling?
Transcription is an asynchronous process. After submitting your audio:
1. You receive a job ID immediately
2. Processing happens in the background (typically 15-30% of audio duration)
3. You check the status periodically until completion

3. Better Examples Needed

Current Issues:

• Uses same example URL across all code samples
• No real-world error scenarios
• Missing example responses

Recommended Additions:

## Example Response
```json
{
  "id": "abc123-def456-ghi789",
  "status": "completed",
  "text": "This is your transcribed audio content...",
  "confidence": 0.95,
  "words": [...],
  "audio_duration": 120.5
}

Error Examples:

# Common error scenarios
if transcript.status == aai.TranscriptStatus.error:
    error_msg = transcript.error
    if "file not found" in error_msg.lower():
        print("Audio file URL is not accessible")
    elif "unsupported format" in error_msg.lower():
        print("Please use MP3, WAV, or M4A format")
    else:
        print(f"Transcription failed: {error_msg}")

4. Improved Structure

Current Structure Issues:

• Code samples are overwhelming at the start
• Prerequisites come after code overview
• Related concepts scattered in notes

Recommended Restructure:

# Transcribe a Pre-recorded Audio File

## What You'll Learn
- Submit audio for transcription
- Handle asynchronous processing
- Retrieve and display results

## Prerequisites
[Move this section up and expand]

## Quick Start
[Simplified 5-line example]

## Step-by-Step Tutorial
[Current detailed steps]

## Advanced Configuration
[Speech models, additional parameters]

## Troubleshooting
[Common errors and solutions]

5. User Pain Points

Identified Pain Points:

a) API Key Management:

## Security Best Practices
⚠️ **Never hardcode API keys in production code**

Use environment variables:
```python
import os
aai.settings.api_key = os.getenv("ASSEMBLYAI_API_KEY")

**b) File Access Issues:**
```markdown
## Audio File Requirements
Your audio file must be:
- ✅ Publicly accessible (if using URL)
- ✅ Under X MB in size
- ✅ In supported format (MP3, WAV, M4A, etc.)
- ✅ Not password-protected

**Testing your URL:** Paste your audio URL in a browser - if it downloads/plays, it will work with our API.

c) Long Processing Times:

## Processing Time Expectations
- **Small files** (< 5 minutes): 30-60 seconds
- **Medium files** (5-30 minutes): 2-10 minutes
- **Large files** (> 30 minutes): 10+ minutes

The polling interval (3 seconds) is optimized for most use cases.

Specific Code Improvements

Error Handling Enhancement

# Better error handling example
try:
    transcript = transcriber.transcribe(audio_file, config)
    if transcript.status == aai.TranscriptStatus.error:
        print(f"❌ Transcription failed: {transcript.error}")
        # Provide specific guidance based on error type
        if "invalid audio url" in transcript.error.lower():
            print("💡 Tip: Ensure your audio URL is publicly accessible")
        exit(1)
    print(f"✅ Transcription completed in {transcript.audio_duration}s of audio")
    print(f"📝 Transcript: {transcript.text}")
except Exception as e:
    print(f"❌ Unexpected error: {e}")

Progress Indication

# Add progress indication for polling
import sys
while True:
    transcript = requests.get(polling_endpoint, headers=headers).json()
    if transcript["status"] == "completed":
        print(f"\n✅ Completed! Transcript: {transcript['text']}")
        break
    elif transcript["status"] == "error":
        print(f"\n❌ Error: {transcript['error']}")
        break
    else:
        print("⏳ Processing...", end="", flush=True)
        time.sleep(3)
        print(".", end="", flush=True)

Quick Wins

1. Add a “Quick Test” section with a 3-line example
2. Include expected output for the sample audio file
3. Add troubleshooting section with common errors
4. Expand prerequisites with system requirements
5. Add security warnings about API key handling
6. Include processing time expectations

Priority Recommendations

1. High Priority: Add missing prerequisites, error handling, and security guidance
2. Medium Priority: Restructure for better flow, add troubleshooting section
3. Low Priority: Enhance examples with more variety and real-world scenarios

This documentation has strong technical content but needs better user experience design to reduce friction for new users.

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