Feedback: speech-to-text-pre-recorded-audio-word-search

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/speech-to-text/pre-recorded-audio/word-search
Category: speech-to-text
Generated: 05/08/2025, 4:23:23 pm

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Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:23:22 pm

Technical Documentation Analysis: Word Search Feature

Overall Assessment

This documentation provides a solid foundation but has several gaps that could frustrate users and lead to implementation issues. The code examples are comprehensive, but the conceptual explanation needs significant improvement.

Critical Issues & Recommendations

1. Missing Information

API Response Structure

• Issue: The documentation doesn’t explain the complete response structure
• Fix: Add a dedicated section showing the full API response:

{
  "id": "transcript_id",
  "total_count": 15,
  "matches": [
    {
      "text": "foo",
      "count": 3,
      "timestamps": [[1000, 1500], [45000, 45500], [120000, 120500]],
      "indexes": [12, 156, 234]
    }
  ]
}

Parameter Constraints

• Issue: Vague constraint description (“up to five words”)
• Fix: Clarify with specific examples:
  • ✅ Valid: ["hello", "world", "hello world", "API key setup"]
  • ❌ Invalid: ["this phrase has more than five words total"]
  • Add character limits, special character handling, case sensitivity rules

Prerequisites

• Issue: No mention of required transcript completion
• Fix: Add clear prerequisite section explaining that transcripts must be in “completed” status

2. Unclear Explanations

Feature Purpose

• Issue: Generic description doesn’t convey real value
• Current: “useful for quickly finding relevant information”
• Better: “Returns exact timestamps and occurrence counts, enabling you to jump directly to relevant audio segments or analyze keyword frequency across your content”

Case Sensitivity

• Issue: Not mentioned at all
• Fix: Explicitly state whether searches are case-sensitive and provide examples

3. Better Examples Needed

Realistic Use Cases Replace generic ["foo", "bar", "foo bar", "42"] with practical examples:

# Customer service analysis
keywords = ["complaint", "refund", "satisfied", "technical issue"]

# Meeting insights
keywords = ["action item", "deadline", "budget", "next steps"]

# Compliance monitoring
keywords = ["confidential", "GDPR", "data breach"]

Error Handling Add examples showing common failure scenarios:

try:
    matches = transcript.word_search(words)
    if not matches:
        print("No matches found for the specified keywords")
except Exception as e:
    print(f"Word search failed: {e}")

4. Structure Improvements

Recommended New Structure:

1. Overview - What it does and why it’s useful
2. Prerequisites - Transcript status requirements
3. Parameters - Detailed constraints and validation rules
4. Response Format - Complete API response structure
5. Usage Examples - Realistic scenarios by programming language
6. Advanced Features - Timestamps, indexes explanation
7. Troubleshooting - Common issues and solutions

5. User Pain Points

Pain Point 1: Timestamp Understanding

• Issue: Users won’t understand timestamp format (milliseconds vs seconds)
• Fix: Add explanation: “Timestamps are in milliseconds from audio start. Convert to seconds by dividing by 1000.”

Pain Point 2: URL Encoding

• Issue: PHP example shows URL encoding, but others don’t mention it
• Fix: Add consistent guidance across all languages about when URL encoding is needed

Pain Point 3: Rate Limiting

• Issue: No mention of API limits for word search requests
• Fix: Add rate limiting information and best practices

Pain Point 4: Empty Results

• Issue: No guidance on handling zero matches
• Fix: Show how to handle empty results and suggest troubleshooting steps

Quick Wins

1. Add a “What You’ll Get” section showing sample output with real data
2. Include timing expectations - “Results typically available within 1-2 seconds”
3. Add parameter validation examples showing what inputs will be rejected
4. Create a troubleshooting table with common issues and solutions
5. Add links to related features like sentiment analysis or entity detection that might use similar keywords

Code Quality Issues

• Inconsistent error handling across language examples
• Missing input validation in most examples
• No async/await best practices shown for JavaScript
• Hardcoded URLs should reference a constants section

These improvements would transform this from basic reference documentation into genuinely helpful guidance that reduces support tickets and improves developer experience.

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